diff --git a/.env.example b/.env.example new file mode 100644 index 0000000000000000000000000000000000000000..25a766138f6d9021e141877cd729cc334bca7121 --- /dev/null +++ b/.env.example @@ -0,0 +1,62 @@ +FIGMENT_MODE=hosted +MODEL_STACK=omni_native +MODEL_BACKEND= +AUDIO_BACKEND=none +ENABLE_AUDIO_INTAKE=false +ALLOW_LOCAL_ASR=false +ALLOW_SELF_HOSTED_OMNI=false + +HF_MODEL_ID=nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16 +NVIDIA_MODEL_ID=nvidia/nemotron-3-nano-omni-30b-a3b-reasoning +NVIDIA_BASE_URL=https://integrate.api.nvidia.com/v1 +NVIDIA_API_KEY= +LOCAL_MODEL_ID=nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16 +HF_ENDPOINT_URL= +OMNI_ENDPOINT_URL= +HF_TOKEN= +LLAMA_BASE_URL=http://127.0.0.1:8001/v1 +FIGMENT_TRACE_DIR=traces +FIGMENT_SMOKE_ALLOW_NETWORK=false +FIGMENT_SMOKE_TIMEOUT_SECONDS=8 +FIGMENT_SMOKE_TRACE_PATH= + +# Hosted-live Omni demo: +# FIGMENT_MODE=hosted +# MODEL_BACKEND=hosted_omni +# NVIDIA_API_KEY=nvapi-... +# AUDIO_BACKEND=omni_native +# ENABLE_AUDIO_INTAKE=true + +# Local/offline proof. This can use the smaller local model, or self-hosted Omni +# on adequate local hardware; smoke output records the configured LOCAL_MODEL_ID. +# FIGMENT_MODE=local +# MODEL_STACK=local_4b_parakeet +# MODEL_BACKEND=llama_cpp +# LLAMA_BASE_URL=http://127.0.0.1:8001/v1 +# LOCAL_MODEL_ID=nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16 +# AUDIO_BACKEND=none +# FIGMENT_SMOKE_ALLOW_NETWORK=true +# +# Evidence bundle after the full-weight local endpoint is live: +# PYTHON_DOTENV_DISABLED=true python3 scripts/run_local_4b_evidence.py --base-url "$LLAMA_BASE_URL" + +# Self-hosted Omni proof on adequate local hardware. This is the technical +# Off the Grid Omni route when the endpoint is local and no cloud APIs are used. +# FIGMENT_MODE=local +# MODEL_STACK=omni_native +# MODEL_BACKEND=llama_cpp +# LOCAL_MODEL_ID=nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16 +# LLAMA_BASE_URL=http://127.0.0.1:8001/v1 +# ALLOW_SELF_HOSTED_OMNI=true + +# Optional local ASR proof. Enable only after Parakeet local ASR passes the gate. +# MODEL_STACK=local_4b_parakeet +# MODEL_BACKEND=llama_cpp +# AUDIO_BACKEND=parakeet_nemo +# ENABLE_AUDIO_INTAKE=true +# ALLOW_LOCAL_ASR=true +# PYTHON_DOTENV_DISABLED=true python3 scripts/run_local_asr_evidence.py --provider-payload + +MODAL_PROFILE= +MISTRAL_API_KEY= +MINIMAX_API_KEY= diff --git a/data/eval/field_workflow_holdout_v1.jsonl b/data/eval/field_workflow_holdout_v1.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c6fc2b50d2e9484ab586e1277ace210c2f8be908 --- /dev/null +++ b/data/eval/field_workflow_holdout_v1.jsonl @@ -0,0 +1,150 @@ +{"case_id": "field_workflow_holdout_v1-000000", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "6d932c8a3b46cff0", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000000", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 100; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 0; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000001", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "a50c31c422ce85f4", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000001", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 101; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 1; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000002", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "4685fa33710122cb", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000002", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 102; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 2; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000003", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e9f5fd259ee5bf4a", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000003", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 103; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 3; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000004", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c059d107ce2db9bf", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000004", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 104; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 4; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000005", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "2b0c9269a0b941f2", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000005", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 105; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 5; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000006", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "ed6299478f208cf6", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000006", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 106; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 6; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000007", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "7bf4a15574d546f8", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000007", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "burn with spreading redness", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 107; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 7; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000008", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "20c49edb94a0e9a0", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000008", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "sudden confusion during shelter check", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 108; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 8; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000009", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "2f959ac120353113", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000009", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "chest pain radiating to shoulder", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 109; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 9; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000010", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "782999cca11e3918", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000010", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "diarrhea with no urine", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "9 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 110; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 10; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "diarrhea, very dry mouth, no urine for many hours, tired but answers questions", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "pulse fast; temperature normal by touch; blood pressure not measured", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000011", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "fc6bc50176088801", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000011", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "fever with stiff neck", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "31 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 111; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 11; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "temperature 102 F with stiff neck and severe body aches", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 102 F; pulse fast; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000012", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "badef840509cce23", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000012", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "postpartum severe headache", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "33 years", "pregnancy_status": "postpartum one week", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 112; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 12; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "severe headache with vision changes and marked swelling of hands", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse regular; temperature pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000013", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "2ae0848f992f3909", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000013", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "marked retractions", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "12 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 113; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 13; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "marked retractions and unable to speak full sentences", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation not available; pulse fast", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000014", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "8fc3ef8aad7b51e5", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000014", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "face droop and speech change", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "69 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 114; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 14; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "facial droop with slurred speech noticed suddenly", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure pending; pulse regular; glucose not available", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000015", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "4b9f5568adbd92cd", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000015", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "wound drainage", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "36 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 115; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 15; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "wound has pus and foul drainage with rapidly worsening pain", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature 100.9 F; pulse fast; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000016", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "35b5921c397dc50a", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000016", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "difficult to arouse on cot", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "58 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 116; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 16; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "briefly unresponsive and difficult to arouse when checked", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "pulse present; respirations shallow by observation; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000017", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "336c08f81de3c12a", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000017", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "chest pressure at cleanup station", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "64 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 117; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 17; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "chest pressure with shortness of breath and sweating for about twenty minutes", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 116 by monitor; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000018", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "53f85869a5af6b81", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000018", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "toddler with poor intake", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "18 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 118; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 18; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "lethargic toddler, poor perfusion noted by responder, unable to keep fluids down", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature not measured; pulse fast; capillary refill description pending", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000019", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"], "expected_red_flag_rule_ids": ["PREG-001", "red_flag_chest_pain", "FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "b528cc13f76eecd9", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000019", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "postpartum fever", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "44 years", "pregnancy_status": "postpartum two weeks", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 119; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 19; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "fever with chills during postpartum period, no chest pain reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.5 F; pulse fast; blood pressure pending", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000020", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "513a0fe8b6195d75", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["PREG-DANGER-SIGNS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000020", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "pregnancy bleeding concern", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "28 years", "pregnancy_status": "pregnant, about 30 weeks by report", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 120; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 20; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "vaginal bleeding and abdominal pain during pregnancy", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure pending; pulse fast by palpation; temperature not measured", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000021", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "73b08dd913756b67", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000021", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "blue lips with breathing difficulty", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "67 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 121; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 21; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "blue lips, severe respiratory distress, tripod positioning", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "oxygen saturation pending; pulse fast; blood pressure not recorded", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000022", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "bf713b00a915d687", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "STROKE-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000022", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "arm weakness with vision change", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "73 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 122; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 22; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "arm weakness with sudden vision change and balance trouble", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "pulse regular; blood pressure pending; temperature normal", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000023", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "0a2b53a7ff98fb69", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000023", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "wound with red streaking", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "41 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 123; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 23; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "leg wound with red streaking and worsening swelling", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature pending; pulse mildly fast; blood pressure not measured", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000024", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "6d84e5bb28dc0b8b", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000024", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 124; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 24; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000025", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e81f38fbfc127fa1", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000025", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 125; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 25; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000026", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f7e5741a064bfa4d", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000026", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 126; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 26; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000027", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f7a4541bc8cde41e", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000027", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 127; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 27; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000028", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "38c56bfcc7a5b490", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000028", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 128; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 28; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000029", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "cb65e731d523e5f7", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000029", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 129; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 29; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000030", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "fe4e8f2cf16d2ffc", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000030", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 130; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 30; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000031", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c407e8e00e8ff0f4", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000031", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "burn with spreading redness", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 131; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 31; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000032", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "827c443b0176ca32", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000032", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "sudden confusion during shelter check", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 132; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 32; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000033", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f8518f9d2891b31d", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000033", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "chest pain radiating to shoulder", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 133; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 33; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000034", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "dedbea7a9eea2678", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000034", "structured_intake": {"allergies": "not yet asked", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "vomiting and possible dehydration", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 234; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 34; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "ped_dehyd_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000035", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "60c90dbf62bde3f2", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000035", "structured_intake": {"allergies": "unknown", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "young infant fever", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 235; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 35; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "fever_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000036", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "6bbbc33a95ddaf63", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000036", "structured_intake": {"allergies": "none reported", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "fainting during pregnancy", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 236; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 36; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "preg_danger_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000037", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "82084311fb8f396e", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000037", "structured_intake": {"allergies": "not yet asked", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "gasping breathing", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 237; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 37; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "resp_distress_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000038", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "STROKE-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "eb39e84572e04d6a", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000038", "structured_intake": {"allergies": "unknown", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "one-sided weakness", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 238; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 38; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "stroke_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000039", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f9ddd7eec8cadc34", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000039", "structured_intake": {"allergies": "none reported", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "burn with spreading redness", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 239; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 39; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "wound_infection_escalation", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000040", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f54a90adca2b05c5", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000040", "structured_intake": {"allergies": "not yet asked", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "sudden confusion during shelter check", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 240; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 40; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "ams_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000041", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "84581629ee7eaee2", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000041", "structured_intake": {"allergies": "unknown", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "chest pain radiating to shoulder", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 241; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 41; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "chest_pain_escalation", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000042", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "68a7ea06650b97b1", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000042", "structured_intake": {"allergies": "not yet asked", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 342; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 42; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000043", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "480eefe501f7f59d", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000043", "structured_intake": {"allergies": "unknown", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 343; the responder confirmed the text before navigation. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 43; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000044", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e20bb0e818ddaa80", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000044", "structured_intake": {"allergies": "none reported", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 344; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 44; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000045", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "35d0e7fe57203f4f", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000045", "structured_intake": {"allergies": "not yet asked", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 345; the responder confirmed the text before navigation. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 45; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000046", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "5b55509ac6aa231d", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000046", "structured_intake": {"allergies": "unknown", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 346; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 46; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000047", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "eff62f80e3939f45", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000047", "structured_intake": {"allergies": "none reported", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "burn with spreading redness", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 347; the responder confirmed the text before navigation. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 47; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000048", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "40b996a7f83a6f4e", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000048", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 148; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 48; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000049", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "590d37648be1acb0", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000049", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 149; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 49; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000050", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["SAFETY-BOUNDARIES-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "a3a03fde7207e825", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000050", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "routine cough review", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "8 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic negation-boundary training case. Confirmed text mentions danger words only as denied or absent facts. Variant 450; no identifiers included. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 50; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "cough after dust exposure; no fever, no shortness of breath, no chest pain, speaking normally", "target_protocol_card_hint": "SAFETY-BOUNDARIES-v1", "vitals": "temperature normal; pulse regular by palpation; respirations unlabored; blood pressure not yet recorded", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "ped_dehyd_red_flags", "safety_boundary"], "target_protocol_card_id": "SAFETY-BOUNDARIES-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields"]} +{"case_id": "field_workflow_holdout_v1-000051", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "4c6b379fb18a6a63", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000051", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 151; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 51; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000052", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "cde41684ba2dccf7", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000052", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 152; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 52; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000053", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "75a1d58d239948d3", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000053", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 153; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 53; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000054", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "3048c1c5266700b4", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000054", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 154; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 54; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields"]} +{"case_id": "field_workflow_holdout_v1-000055", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["SAFETY-BOUNDARIES-v1"], "expected_min_protocol_urgency": "routine", "expected_missing_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": [], "expected_source_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e3334d99535f96b9", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000055", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "pregnancy status clarification", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "34 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic negation-boundary training case. Confirmed text mentions danger words only as denied or absent facts. Variant 455; no identifiers included. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 55; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "not pregnant and denies bleeding, severe headache, vision change, abdominal pain, or fever", "target_protocol_card_hint": "SAFETY-BOUNDARIES-v1", "vitals": "temperature normal; pulse regular by palpation; respirations unlabored; blood pressure not yet recorded", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "wound_infection_escalation", "safety_boundary"], "target_protocol_card_id": "SAFETY-BOUNDARIES-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields"]} +{"case_id": "field_workflow_holdout_v1-000056", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "2501aaa11f0604fc", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000056", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "sudden confusion during shelter check", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 156; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 56; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000057", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c3e2bd646f21747d", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000057", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "chest pain radiating to shoulder", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 157; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 57; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000058", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c21710fff6c353c0", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000058", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "diarrhea with no urine", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "not yet asked", "patient_age": "9 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 158; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 58; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "diarrhea, very dry mouth, no urine for many hours, tired but answers questions", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "pulse fast; temperature normal by touch; blood pressure not measured", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000059", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "58c6cf31cc83c99b", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["FEVER-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000059", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "fever with stiff neck", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "31 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 159; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 59; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "temperature 102 F with stiff neck and severe body aches", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 102 F; pulse fast; blood pressure pending", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000060", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["SAFETY-BOUNDARIES-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "ecd69fd8c519a46f", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000060", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "pediatric hydration reassurance request", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "29 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic negation-boundary training case. Confirmed text mentions danger words only as denied or absent facts. Variant 460; no identifiers included. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 60; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "child drank water; no lethargy, no sunken eyes, no very dry mouth, urine this afternoon", "target_protocol_card_hint": "SAFETY-BOUNDARIES-v1", "vitals": "temperature normal; pulse regular by palpation; respirations unlabored; blood pressure not yet recorded", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "preg_danger_signs", "safety_boundary"], "target_protocol_card_id": "SAFETY-BOUNDARIES-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields"]} +{"case_id": "field_workflow_holdout_v1-000061", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "85814309aaabc0a1", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000061", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "marked retractions", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "not yet asked", "patient_age": "12 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 161; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 61; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "marked retractions and unable to speak full sentences", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation not available; pulse fast", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000062", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "fa8cee5ecfc585f0", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000062", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "face droop and speech change", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "unknown", "patient_age": "69 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 162; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 62; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "facial droop with slurred speech noticed suddenly", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure pending; pulse regular; glucose not available", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000063", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "148cc1b54cacd5d5", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000063", "structured_intake": {"allergies": "unknown", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "wound drainage", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "none reported", "patient_age": "36 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 163; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 63; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "wound has pus and foul drainage with rapidly worsening pain", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature 100.9 F; pulse fast; blood pressure pending", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000064", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "0c77a8afec80084e", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000064", "structured_intake": {"allergies": "none reported", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "difficult to arouse on cot", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "not yet asked", "patient_age": "58 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 164; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 64; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "briefly unresponsive and difficult to arouse when checked", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "pulse present; respirations shallow by observation; blood pressure pending", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000065", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f46a894b03eb9f8c", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000065", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "chest pressure at cleanup station", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "unknown", "patient_age": "64 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 165; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 65; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "chest pressure with shortness of breath and sweating for about twenty minutes", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 116 by monitor; blood pressure pending", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000066", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "923fd1a0b24fa65d", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000066", "structured_intake": {"allergies": "unknown", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "toddler with poor intake", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "none reported", "patient_age": "18 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 166; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 66; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "lethargic toddler, poor perfusion noted by responder, unable to keep fluids down", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature not measured; pulse fast; capillary refill description pending", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000067", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"], "expected_red_flag_rule_ids": ["PREG-001", "red_flag_chest_pain", "FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "68535beb199422e0", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000067", "structured_intake": {"allergies": "none reported", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "postpartum fever", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "not yet asked", "patient_age": "44 years", "pregnancy_status": "postpartum two weeks", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 167; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 67; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "fever with chills during postpartum period, no chest pain reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.5 F; pulse fast; blood pressure pending", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000068", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "39f5df3d50dff14a", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000068", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "pregnancy bleeding concern", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "unknown", "patient_age": "28 years", "pregnancy_status": "pregnant, about 30 weeks by report", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 168; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 68; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "vaginal bleeding and abdominal pain during pregnancy", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure pending; pulse fast by palpation; temperature not measured", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000069", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "5ca9cf259329b43b", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000069", "structured_intake": {"allergies": "unknown", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "blue lips with breathing difficulty", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "none reported", "patient_age": "67 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 169; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 69; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "blue lips, severe respiratory distress, tripod positioning", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "oxygen saturation pending; pulse fast; blood pressure not recorded", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000070", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "035a42d9a9a20225", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000070", "structured_intake": {"allergies": "none reported", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "arm weakness with vision change", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "not yet asked", "patient_age": "73 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 170; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 70; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "arm weakness with sudden vision change and balance trouble", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "pulse regular; blood pressure pending; temperature normal", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000071", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "a06ef5b4cdb147f2", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000071", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "wound with red streaking", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "unknown", "patient_age": "41 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 171; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 71; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "leg wound with red streaking and worsening swelling", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature pending; pulse mildly fast; blood pressure not measured", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000072", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e44a4cb5390a0ed6", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000072", "structured_intake": {"allergies": "unknown", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 172; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 72; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000073", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "820f091f6ad816b0", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000073", "structured_intake": {"allergies": "none reported", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 173; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 73; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000074", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "9a45157b4f967b7c", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000074", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 174; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 74; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000075", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "45a78a37d16d60c9", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000075", "structured_intake": {"allergies": "unknown", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 175; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 75; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000076", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "610480e49649e0cd", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000076", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "pregnancy bleeding concern", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "unknown", "patient_age": "28 years", "pregnancy_status": "pregnant, about 30 weeks by report", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 276; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 76; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "vaginal bleeding and abdominal pain during pregnancy", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "blood pressure pending; pulse fast by palpation; temperature not measured", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "preg_danger_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000077", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c13e82006fe4225c", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000077", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "blue lips with breathing difficulty", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "none reported", "patient_age": "67 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 277; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 77; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "blue lips, severe respiratory distress, tripod positioning", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "oxygen saturation pending; pulse fast; blood pressure not recorded", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "resp_distress_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000078", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "STROKE-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e8a8ffcc5ee44f25", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000078", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "arm weakness with vision change", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "not yet asked", "patient_age": "73 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 278; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 78; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "arm weakness with sudden vision change and balance trouble", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "pulse regular; blood pressure pending; temperature normal", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "stroke_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000079", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "01e9080bf2c97d93", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000079", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "wound with red streaking", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "unknown", "patient_age": "41 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 279; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 79; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "leg wound with red streaking and worsening swelling", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature pending; pulse mildly fast; blood pressure not measured", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "wound_infection_escalation", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000080", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "8390be1838c098ad", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000080", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 280; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 80; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "ams_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000081", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f4b5b0a9d5b007c9", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000081", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 281; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 81; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "chest_pain_escalation", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000082", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "680de34ad6871b23", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000082", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 282; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 82; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "ped_dehyd_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000083", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "2fdc29ed383e56c2", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000083", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 283; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 83; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "fever_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000084", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "51687f18040365fc", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000084", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 284; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 84; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "preg_danger_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000085", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "49f3d0bfd7e57d85", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000085", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 285; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 85; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "resp_distress_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000086", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "2a8b46f9e341eb6c", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000086", "structured_intake": {"allergies": "not yet asked", "available_supplies": "protocol binder with relevant and distractor cards, radio", "chief_concern": "face droop and speech change", "confirmed": true, "field_workflow_goal": "cite only relevant retrieved cards and avoid distractor leakage.", "medications": "unknown", "patient_age": "69 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 186; the responder confirmed the text before navigation. V3 field-workflow category: source_card_discipline. Goal: cite only relevant retrieved cards and avoid distractor leakage. Variant 86; synthetic and de-identified.", "setting": "paper protocol binder review desk", "symptoms": "facial droop with slurred speech noticed suddenly", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure pending; pulse regular; glucose not available", "workflow_category": "source_card_discipline"}, "tags": ["field_workflow", "source_card_discipline", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "source_card_discipline", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000087", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "246f3791a27006cd", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000087", "structured_intake": {"allergies": "unknown", "available_supplies": "protocol binder with relevant and distractor cards, radio", "chief_concern": "wound drainage", "confirmed": true, "field_workflow_goal": "cite only relevant retrieved cards and avoid distractor leakage.", "medications": "none reported", "patient_age": "36 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 187; the responder confirmed the text before navigation. V3 field-workflow category: source_card_discipline. Goal: cite only relevant retrieved cards and avoid distractor leakage. Variant 87; synthetic and de-identified.", "setting": "paper protocol binder review desk", "symptoms": "wound has pus and foul drainage with rapidly worsening pain", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature 100.9 F; pulse fast; blood pressure pending", "workflow_category": "source_card_discipline"}, "tags": ["field_workflow", "source_card_discipline", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "source_card_discipline", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000088", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "88fa25e19a37b301", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000088", "structured_intake": {"allergies": "none reported", "available_supplies": "protocol binder with relevant and distractor cards, radio", "chief_concern": "difficult to arouse on cot", "confirmed": true, "field_workflow_goal": "cite only relevant retrieved cards and avoid distractor leakage.", "medications": "not yet asked", "patient_age": "58 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 188; the responder confirmed the text before navigation. V3 field-workflow category: source_card_discipline. Goal: cite only relevant retrieved cards and avoid distractor leakage. Variant 88; synthetic and de-identified.", "setting": "paper protocol binder review desk", "symptoms": "briefly unresponsive and difficult to arouse when checked", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "pulse present; respirations shallow by observation; blood pressure pending", "workflow_category": "source_card_discipline"}, "tags": ["field_workflow", "source_card_discipline", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "source_card_discipline", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000089", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "30f459230fcf8b51", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000089", "structured_intake": {"allergies": "not yet asked", "available_supplies": "protocol binder with relevant and distractor cards, radio", "chief_concern": "chest pressure at cleanup station", "confirmed": true, "field_workflow_goal": "cite only relevant retrieved cards and avoid distractor leakage.", "medications": "unknown", "patient_age": "64 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 189; the responder confirmed the text before navigation. V3 field-workflow category: source_card_discipline. Goal: cite only relevant retrieved cards and avoid distractor leakage. Variant 89; synthetic and de-identified.", "setting": "paper protocol binder review desk", "symptoms": "chest pressure with shortness of breath and sweating for about twenty minutes", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 116 by monitor; blood pressure pending", "workflow_category": "source_card_discipline"}, "tags": ["field_workflow", "source_card_discipline", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "source_card_discipline", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000090", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c9e78e94061743e0", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000090", "structured_intake": {"allergies": "unknown", "available_supplies": "protocol binder with relevant and distractor cards, radio", "chief_concern": "toddler with poor intake", "confirmed": true, "field_workflow_goal": "cite only relevant retrieved cards and avoid distractor leakage.", "medications": "none reported", "patient_age": "18 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 190; the responder confirmed the text before navigation. V3 field-workflow category: source_card_discipline. Goal: cite only relevant retrieved cards and avoid distractor leakage. Variant 90; synthetic and de-identified.", "setting": "paper protocol binder review desk", "symptoms": "lethargic toddler, poor perfusion noted by responder, unable to keep fluids down", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature not measured; pulse fast; capillary refill description pending", "workflow_category": "source_card_discipline"}, "tags": ["field_workflow", "source_card_discipline", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "source_card_discipline", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000091", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"], "expected_red_flag_rule_ids": ["PREG-001", "red_flag_chest_pain", "FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "8c07fea011c52661", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000091", "structured_intake": {"allergies": "none reported", "available_supplies": "protocol binder with relevant and distractor cards, radio", "chief_concern": "postpartum fever", "confirmed": true, "field_workflow_goal": "cite only relevant retrieved cards and avoid distractor leakage.", "medications": "not yet asked", "patient_age": "44 years", "pregnancy_status": "postpartum two weeks", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 191; the responder confirmed the text before navigation. V3 field-workflow category: source_card_discipline. Goal: cite only relevant retrieved cards and avoid distractor leakage. Variant 91; synthetic and de-identified.", "setting": "paper protocol binder review desk", "symptoms": "fever with chills during postpartum period, no chest pain reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.5 F; pulse fast; blood pressure pending", "workflow_category": "source_card_discipline"}, "tags": ["field_workflow", "source_card_discipline", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "source_card_discipline", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000092", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f68646a17425e254", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000092", "structured_intake": {"allergies": "not yet asked", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "pregnancy bleeding concern", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "unknown", "patient_age": "28 years", "pregnancy_status": "pregnant, about 30 weeks by report", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 192; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 92; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "vaginal bleeding and abdominal pain during pregnancy", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure pending; pulse fast by palpation; temperature not measured", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000093", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "b4b8691e281a8b35", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000093", "structured_intake": {"allergies": "unknown", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "blue lips with breathing difficulty", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "none reported", "patient_age": "67 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 193; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 93; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "blue lips, severe respiratory distress, tripod positioning", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "oxygen saturation pending; pulse fast; blood pressure not recorded", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000094", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "303d01ea925b96b0", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000094", "structured_intake": {"allergies": "none reported", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "arm weakness with vision change", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "not yet asked", "patient_age": "73 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 194; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 94; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "arm weakness with sudden vision change and balance trouble", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "pulse regular; blood pressure pending; temperature normal", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000095", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "7cc32b637630588c", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000095", "structured_intake": {"allergies": "not yet asked", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "wound with red streaking", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "unknown", "patient_age": "41 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 195; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 95; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "leg wound with red streaking and worsening swelling", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature pending; pulse mildly fast; blood pressure not measured", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000096", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c772c1b9d8334a0f", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000096", "structured_intake": {"allergies": "unknown", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 196; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 96; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000097", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "666fd9518b934ab8", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000097", "structured_intake": {"allergies": "none reported", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 197; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 97; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000098", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "793503bff3079a85", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000098", "structured_intake": {"allergies": "not yet asked", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 198; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 98; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000099", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations"], "expected_red_flag_rule_ids": ["PREG-001", "red_flag_chest_pain", "FEVER-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "FEVER-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "be1793be4b015043", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000099", "structured_intake": {"allergies": "none reported", "available_supplies": "previous navigator output, protocol binder, radio, paper handoff form", "chief_concern": "postpartum fever", "confirmed": true, "field_workflow_goal": "repair only weak fields while preserving validated facts.", "medications": "not yet asked", "patient_age": "44 years", "pregnancy_status": "postpartum two weeks", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 599; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: workflow_repair_seed. Goal: repair only weak fields while preserving validated facts. Variant 99; synthetic and de-identified.", "setting": "handoff repair desk after weak navigator output", "symptoms": "fever with chills during postpartum period, no chest pain reported", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature 101.5 F; pulse fast; blood pressure pending", "workflow_category": "workflow_repair_seed"}, "tags": ["field_workflow", "workflow_repair_seed", "fever_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "workflow_repair_seed", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000100", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "9b14420bde5dceeb", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000100", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 200; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 100; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000101", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c8806e9964ac76c6", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000101", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 201; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 101; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000102", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "8c844bfac2115799", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000102", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 202; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 102; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000103", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "01e329c2cf911825", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000103", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "burn with spreading redness", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 203; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 103; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000104", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "abe0660537feea03", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000104", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "sudden confusion during shelter check", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 204; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 104; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000105", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "28657465450c8450", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000105", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "chest pain radiating to shoulder", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 205; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 105; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000106", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c66a04a6be18f05a", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000106", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "diarrhea with no urine", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "9 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 206; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 106; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "diarrhea, very dry mouth, no urine for many hours, tired but answers questions", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "pulse fast; temperature normal by touch; blood pressure not measured", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000107", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "54d006aab9f86839", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000107", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "fever with stiff neck", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "31 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 207; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 107; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "temperature 102 F with stiff neck and severe body aches", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 102 F; pulse fast; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000108", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "4621e85851d791a5", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000108", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "postpartum severe headache", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "33 years", "pregnancy_status": "postpartum one week", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 208; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 108; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "severe headache with vision changes and marked swelling of hands", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse regular; temperature pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000109", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "eed5a4c70f6751be", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000109", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "marked retractions", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "12 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 209; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 109; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "marked retractions and unable to speak full sentences", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation not available; pulse fast", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000110", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "2ba7c4b0eb0d2caf", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000110", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "face droop and speech change", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "69 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 210; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 110; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "facial droop with slurred speech noticed suddenly", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure pending; pulse regular; glucose not available", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000111", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "319610807e77bde2", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000111", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "wound drainage", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "36 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 211; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 111; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "wound has pus and foul drainage with rapidly worsening pain", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature 100.9 F; pulse fast; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000112", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e6ec1c110b730f52", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000112", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "difficult to arouse on cot", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "58 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 212; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 112; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "briefly unresponsive and difficult to arouse when checked", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "pulse present; respirations shallow by observation; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000113", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "41cb15407888fc85", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000113", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "chest pressure at cleanup station", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "64 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 213; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 113; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "chest pressure with shortness of breath and sweating for about twenty minutes", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 116 by monitor; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000114", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "82a3ee65d1accd2f", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000114", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "toddler with poor intake", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "18 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 214; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 114; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "lethargic toddler, poor perfusion noted by responder, unable to keep fluids down", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature not measured; pulse fast; capillary refill description pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000115", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"], "expected_red_flag_rule_ids": ["PREG-001", "red_flag_chest_pain", "FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c66e731af3f770c9", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000115", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "postpartum fever", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "44 years", "pregnancy_status": "postpartum two weeks", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 215; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 115; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "fever with chills during postpartum period, no chest pain reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.5 F; pulse fast; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000116", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e2df94699d09ff29", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000116", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "pregnancy bleeding concern", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "28 years", "pregnancy_status": "pregnant, about 30 weeks by report", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 216; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 116; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "vaginal bleeding and abdominal pain during pregnancy", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure pending; pulse fast by palpation; temperature not measured", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000117", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "13b9cddb4e0be325", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000117", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "blue lips with breathing difficulty", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "67 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 217; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 117; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "blue lips, severe respiratory distress, tripod positioning", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "oxygen saturation pending; pulse fast; blood pressure not recorded", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000118", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "8a0f4c7bc2e4a6fc", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "STROKE-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000118", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "arm weakness with vision change", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "73 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 218; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 118; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "arm weakness with sudden vision change and balance trouble", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "pulse regular; blood pressure pending; temperature normal", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000119", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "9dc607d4db7f180c", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000119", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "wound with red streaking", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "41 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 219; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 119; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "leg wound with red streaking and worsening swelling", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature pending; pulse mildly fast; blood pressure not measured", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000120", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "049de73cbac47416", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000120", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 220; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 120; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000121", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "24e73ec19819eab2", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000121", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 221; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 121; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000122", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "bc9f1ab9a0a0c6b9", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000122", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 222; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 122; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000123", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "010ac94e9335298a", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000123", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 223; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 123; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000124", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "75e42f493e89fde7", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000124", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 224; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 124; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000125", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "7a9c3e267d950624", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000125", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 225; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 125; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000126", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "6bd04c1630ba4dc7", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000126", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 226; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 126; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000127", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "04a9f3e0102b21cd", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000127", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "burn with spreading redness", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 227; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 127; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000128", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f297a0786d4df118", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000128", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "sudden confusion during shelter check", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 228; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 128; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000129", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "91e155777d80f214", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000129", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "chest pain radiating to shoulder", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 229; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 129; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000130", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f06025a4db005b53", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000130", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "diarrhea with no urine", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "9 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 230; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 130; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "diarrhea, very dry mouth, no urine for many hours, tired but answers questions", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "pulse fast; temperature normal by touch; blood pressure not measured", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000131", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "6d080f0e82f8f7ed", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000131", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "fever with stiff neck", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "31 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 231; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 131; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "temperature 102 F with stiff neck and severe body aches", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 102 F; pulse fast; blood pressure pending", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000132", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "5c8653713b543378", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000132", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "postpartum severe headache", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "33 years", "pregnancy_status": "postpartum one week", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 232; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 132; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "severe headache with vision changes and marked swelling of hands", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse regular; temperature pending", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000133", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c1e6b721e4a5cb31", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000133", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "marked retractions", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "12 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 233; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 133; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "marked retractions and unable to speak full sentences", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation not available; pulse fast", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"case_id": "field_workflow_holdout_v1-000134", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "STROKE-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "9513b7f6cbbc48b7", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000134", "structured_intake": {"allergies": "unknown", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "one-sided weakness", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 334; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 134; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "stroke_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000135", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "20568b0ea60718aa", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000135", "structured_intake": {"allergies": "none reported", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "burn with spreading redness", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 335; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 135; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "wound_infection_escalation", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000136", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "7f8d00c81f2080c0", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000136", "structured_intake": {"allergies": "not yet asked", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "sudden confusion during shelter check", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 336; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 136; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "ams_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000137", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "7b5b9933bc461771", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000137", "structured_intake": {"allergies": "unknown", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "chest pain radiating to shoulder", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 337; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 137; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "chest_pain_escalation", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000138", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "b9ca96c041276e9e", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000138", "structured_intake": {"allergies": "none reported", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "diarrhea with no urine", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "not yet asked", "patient_age": "9 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 338; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 138; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "diarrhea, very dry mouth, no urine for many hours, tired but answers questions", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "pulse fast; temperature normal by touch; blood pressure not measured", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "ped_dehyd_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000139", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "0dfe22bd6cc8169b", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000139", "structured_intake": {"allergies": "not yet asked", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "fever with stiff neck", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "unknown", "patient_age": "31 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 339; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 139; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "temperature 102 F with stiff neck and severe body aches", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature 102 F; pulse fast; blood pressure pending", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "fever_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000140", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "ad98de8b5990208c", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000140", "structured_intake": {"allergies": "unknown", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "postpartum severe headache", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "none reported", "patient_age": "33 years", "pregnancy_status": "postpartum one week", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 340; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 140; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "severe headache with vision changes and marked swelling of hands", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "blood pressure not yet measured; pulse regular; temperature pending", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "preg_danger_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000141", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e568f4f3470705be", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000141", "structured_intake": {"allergies": "none reported", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "marked retractions", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "not yet asked", "patient_age": "12 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 341; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 141; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "marked retractions and unable to speak full sentences", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "respiratory rate not counted; oxygen saturation not available; pulse fast", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "resp_distress_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"case_id": "field_workflow_holdout_v1-000142", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "ec6e3312105b3b54", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000142", "structured_intake": {"allergies": "unknown", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 442; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 142; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"case_id": "field_workflow_holdout_v1-000143", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "1d8be63f441de52b", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000143", "structured_intake": {"allergies": "none reported", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "burn with spreading redness", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 443; the responder confirmed the text before navigation. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 143; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"case_id": "field_workflow_holdout_v1-000144", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "5235fdc5ccee2ddf", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000144", "structured_intake": {"allergies": "not yet asked", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "sudden confusion during shelter check", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 444; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 144; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"case_id": "field_workflow_holdout_v1-000145", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e1d06301e9fd4f70", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000145", "structured_intake": {"allergies": "unknown", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "chest pain radiating to shoulder", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 445; the responder confirmed the text before navigation. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 145; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"case_id": "field_workflow_holdout_v1-000146", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "bc1e34979b34b8fe", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000146", "structured_intake": {"allergies": "none reported", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "diarrhea with no urine", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "not yet asked", "patient_age": "9 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 446; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 146; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "diarrhea, very dry mouth, no urine for many hours, tired but answers questions", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "pulse fast; temperature normal by touch; blood pressure not measured", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"case_id": "field_workflow_holdout_v1-000147", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c9a90911730305d2", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000147", "structured_intake": {"allergies": "not yet asked", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "fever with stiff neck", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "unknown", "patient_age": "31 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 447; the responder confirmed the text before navigation. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 147; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "temperature 102 F with stiff neck and severe body aches", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "temperature 102 F; pulse fast; blood pressure pending", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"case_id": "field_workflow_holdout_v1-000148", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "b232d360d0048e0c", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000148", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 248; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 148; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"case_id": "field_workflow_holdout_v1-000149", "dataset_version": "field_workflow_holdout_v1", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "785e84970fd13006", "prompt_template_hash": "671e3ab4292161e8", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000149", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 249; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 149; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} diff --git a/data/eval/field_workflow_holdout_v1_corrected_scoring.jsonl b/data/eval/field_workflow_holdout_v1_corrected_scoring.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9e8e2d430784b51ef978b6c91f790942a1e03ffd --- /dev/null +++ b/data/eval/field_workflow_holdout_v1_corrected_scoring.jsonl @@ -0,0 +1,150 @@ +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000000", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "d4775428acc8fa98", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000000", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 100; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 0; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000001", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "b6c5e694ee19ca34", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000001", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 101; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 1; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000002", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "94b28617c3461478", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000002", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 102; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 2; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000003", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "b439628eae71446c", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000003", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 103; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 3; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000004", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "3c8a44b3cb106f88", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000004", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 104; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 4; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000005", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "66794c043764c9ba", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000005", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 105; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 5; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000006", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f54fca4bd86a2119", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000006", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 106; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 6; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000007", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "8f56d2229cd3d574", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000007", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "burn with spreading redness", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 107; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 7; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000008", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "13f32172c24e6a31", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000008", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "sudden confusion during shelter check", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 108; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 8; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000009", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "5874936377e13613", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000009", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "chest pain radiating to shoulder", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 109; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 9; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000010", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "a75acf76b900265a", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000010", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "diarrhea with no urine", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "9 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 110; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 10; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "diarrhea, very dry mouth, no urine for many hours, tired but answers questions", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "pulse fast; temperature normal by touch; blood pressure not measured", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000011", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "cff3447010e5786e", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000011", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "fever with stiff neck", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "31 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 111; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 11; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "temperature 102 F with stiff neck and severe body aches", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 102 F; pulse fast; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000012", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "bf0c1346e2f08093", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000012", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "postpartum severe headache", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "33 years", "pregnancy_status": "postpartum one week", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 112; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 12; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "severe headache with vision changes and marked swelling of hands", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse regular; temperature pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000013", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "891b88166d5a3762", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000013", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "marked retractions", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "12 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 113; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 13; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "marked retractions and unable to speak full sentences", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation not available; pulse fast", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000014", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "54f842397712f6f3", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000014", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "face droop and speech change", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "69 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 114; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 14; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "facial droop with slurred speech noticed suddenly", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure pending; pulse regular; glucose not available", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000015", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "409498f8adf62075", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000015", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "wound drainage", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "36 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 115; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 15; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "wound has pus and foul drainage with rapidly worsening pain", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature 100.9 F; pulse fast; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000016", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "47481b715b9e920d", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000016", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "difficult to arouse on cot", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "58 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 116; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 16; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "briefly unresponsive and difficult to arouse when checked", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "pulse present; respirations shallow by observation; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000017", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "82837a667ea5c010", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000017", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "chest pressure at cleanup station", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "64 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 117; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 17; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "chest pressure with shortness of breath and sweating for about twenty minutes", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 116 by monitor; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000018", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "5bd62e6d89214a6a", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000018", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "toddler with poor intake", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "18 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 118; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 18; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "lethargic toddler, poor perfusion noted by responder, unable to keep fluids down", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature not measured; pulse fast; capillary refill description pending", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000019", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report"], "expected_red_flag_rule_ids": ["PREG-001", "FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "8208d01300960ba5", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000019", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "postpartum fever", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "44 years", "pregnancy_status": "postpartum two weeks", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 119; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 19; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "fever with chills during postpartum period, no chest pain reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.5 F; pulse fast; blood pressure pending", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000020", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "5c6555fa1708092a", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["PREG-DANGER-SIGNS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000020", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "pregnancy bleeding concern", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "28 years", "pregnancy_status": "pregnant, about 30 weeks by report", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 120; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 20; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "vaginal bleeding and abdominal pain during pregnancy", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure pending; pulse fast by palpation; temperature not measured", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000021", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "ea72648783b2558d", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000021", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "blue lips with breathing difficulty", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "67 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 121; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 21; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "blue lips, severe respiratory distress, tripod positioning", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "oxygen saturation pending; pulse fast; blood pressure not recorded", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000022", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "b527750038e51952", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "STROKE-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000022", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "arm weakness with vision change", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "73 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 122; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 22; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "arm weakness with sudden vision change and balance trouble", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "pulse regular; blood pressure pending; temperature normal", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000023", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "84b595dd8d313773", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000023", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "wound with red streaking", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "41 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 123; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 23; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "leg wound with red streaking and worsening swelling", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature pending; pulse mildly fast; blood pressure not measured", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000024", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "1ced98220f10aa27", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000024", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 124; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 24; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000025", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "0e201ed34aadbf43", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000025", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 125; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 25; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000026", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e8f91a185cc4011f", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000026", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 126; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 26; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000027", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "8b1de401581597d0", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000027", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 127; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 27; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000028", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f0d1a55dd5978cd9", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000028", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 128; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 28; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000029", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "dce9c9aa10b176ea", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000029", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 129; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 29; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000030", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "16bf272ad00d8888", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000030", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 130; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 30; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000031", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "fbbdd07f6aab8d1e", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000031", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "burn with spreading redness", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 131; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 31; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000032", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "02f7e93ed0c7254d", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000032", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "sudden confusion during shelter check", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 132; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 32; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000033", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "1ef7518c70e9adef", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000033", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "chest pain radiating to shoulder", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 133; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 33; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000034", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "5c39654b10b8a5f7", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000034", "structured_intake": {"allergies": "not yet asked", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "vomiting and possible dehydration", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 234; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 34; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "ped_dehyd_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000035", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "9737a93b3282fc99", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000035", "structured_intake": {"allergies": "unknown", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "young infant fever", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 235; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 35; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "fever_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000036", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "527d6abc0966d974", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000036", "structured_intake": {"allergies": "none reported", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "fainting during pregnancy", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 236; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 36; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "preg_danger_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000037", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "289375c73b6b4677", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000037", "structured_intake": {"allergies": "not yet asked", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "gasping breathing", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 237; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 37; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "resp_distress_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000038", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "STROKE-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "3513de95cfc68148", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000038", "structured_intake": {"allergies": "unknown", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "one-sided weakness", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 238; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 38; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "stroke_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000039", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "a97e9e8c79e9bdda", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000039", "structured_intake": {"allergies": "none reported", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "burn with spreading redness", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 239; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 39; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "wound_infection_escalation", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000040", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "544df8157e467037", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000040", "structured_intake": {"allergies": "not yet asked", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "sudden confusion during shelter check", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 240; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 40; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "ams_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000041", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "8b729b9d1bca54e4", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000041", "structured_intake": {"allergies": "unknown", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "chest pain radiating to shoulder", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 241; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 41; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "chest_pain_escalation", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000042", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "cd83dd349795cfc0", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000042", "structured_intake": {"allergies": "not yet asked", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 342; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 42; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000043", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "ac52fc76c8d349f8", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000043", "structured_intake": {"allergies": "unknown", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 343; the responder confirmed the text before navigation. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 43; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000044", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "9b6a59cdafc7000e", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000044", "structured_intake": {"allergies": "none reported", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 344; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 44; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000045", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "875d73d5f8491fd1", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000045", "structured_intake": {"allergies": "not yet asked", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 345; the responder confirmed the text before navigation. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 45; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000046", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "fb832ec0168ee5b7", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000046", "structured_intake": {"allergies": "unknown", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 346; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 46; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000047", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "400e8a9166a1c9bf", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000047", "structured_intake": {"allergies": "none reported", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "burn with spreading redness", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 347; the responder confirmed the text before navigation. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 47; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000048", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "ed8899adfd317f67", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000048", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 148; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 48; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000049", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "28afd3168aa8440d", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000049", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 149; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 49; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000050", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["SAFETY-BOUNDARIES-v1"], "expected_min_protocol_urgency": "routine", "expected_missing_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": [], "expected_source_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "4b74f8166eb08d69", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000050", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "routine cough review", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "8 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic negation-boundary training case. Confirmed text mentions danger words only as denied or absent facts. Variant 450; no identifiers included. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 50; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "cough after dust exposure; no fever, no shortness of breath, no chest pain, speaking normally", "target_protocol_card_hint": "SAFETY-BOUNDARIES-v1", "vitals": "temperature normal; pulse regular by palpation; respirations unlabored; blood pressure not yet recorded", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "ped_dehyd_red_flags", "safety_boundary"], "target_protocol_card_id": "SAFETY-BOUNDARIES-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000051", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "4fd969792a6d3751", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000051", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 151; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 51; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000052", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "4d939d00ef283ac9", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000052", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 152; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 52; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000053", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "90e5ed3f532314e8", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000053", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 153; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 53; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000054", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "2071f09b29827506", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000054", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 154; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 54; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000055", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["SAFETY-BOUNDARIES-v1"], "expected_min_protocol_urgency": "routine", "expected_missing_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": [], "expected_source_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "12fe788f7566db79", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000055", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "pregnancy status clarification", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "34 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic negation-boundary training case. Confirmed text mentions danger words only as denied or absent facts. Variant 455; no identifiers included. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 55; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "not pregnant and denies bleeding, severe headache, vision change, abdominal pain, or fever", "target_protocol_card_hint": "SAFETY-BOUNDARIES-v1", "vitals": "temperature normal; pulse regular by palpation; respirations unlabored; blood pressure not yet recorded", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "wound_infection_escalation", "safety_boundary"], "target_protocol_card_id": "SAFETY-BOUNDARIES-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000056", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "2ea412e268933912", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000056", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "sudden confusion during shelter check", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 156; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 56; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000057", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "3ec27d4891d5d7de", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000057", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "chest pain radiating to shoulder", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 157; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 57; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000058", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "7110d92b6da5dac8", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000058", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "diarrhea with no urine", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "not yet asked", "patient_age": "9 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 158; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 58; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "diarrhea, very dry mouth, no urine for many hours, tired but answers questions", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "pulse fast; temperature normal by touch; blood pressure not measured", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000059", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "44bf5c408049f536", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["FEVER-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000059", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "fever with stiff neck", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "31 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 159; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 59; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "temperature 102 F with stiff neck and severe body aches", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 102 F; pulse fast; blood pressure pending", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000060", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["SAFETY-BOUNDARIES-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "8d582bd85d0cd3d1", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000060", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "pediatric hydration reassurance request", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "29 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic negation-boundary training case. Confirmed text mentions danger words only as denied or absent facts. Variant 460; no identifiers included. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 60; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "child drank water; no lethargy, no sunken eyes, no very dry mouth, urine this afternoon", "target_protocol_card_hint": "SAFETY-BOUNDARIES-v1", "vitals": "temperature normal; pulse regular by palpation; respirations unlabored; blood pressure not yet recorded", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "preg_danger_signs", "safety_boundary"], "target_protocol_card_id": "SAFETY-BOUNDARIES-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000061", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "3ce963065f3c5477", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000061", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "marked retractions", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "not yet asked", "patient_age": "12 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 161; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 61; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "marked retractions and unable to speak full sentences", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation not available; pulse fast", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000062", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "7ecf81cd513951c3", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000062", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "face droop and speech change", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "unknown", "patient_age": "69 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 162; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 62; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "facial droop with slurred speech noticed suddenly", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure pending; pulse regular; glucose not available", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000063", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "73ded2379732f692", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000063", "structured_intake": {"allergies": "unknown", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "wound drainage", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "none reported", "patient_age": "36 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 163; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 63; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "wound has pus and foul drainage with rapidly worsening pain", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature 100.9 F; pulse fast; blood pressure pending", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000064", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "b1c1eb6e0392dbbf", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000064", "structured_intake": {"allergies": "none reported", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "difficult to arouse on cot", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "not yet asked", "patient_age": "58 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 164; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 64; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "briefly unresponsive and difficult to arouse when checked", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "pulse present; respirations shallow by observation; blood pressure pending", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000065", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "ba2a2ff5d69dbcf5", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000065", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "chest pressure at cleanup station", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "unknown", "patient_age": "64 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 165; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 65; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "chest pressure with shortness of breath and sweating for about twenty minutes", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 116 by monitor; blood pressure pending", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000066", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e50ed699cd60adf8", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000066", "structured_intake": {"allergies": "unknown", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "toddler with poor intake", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "none reported", "patient_age": "18 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 166; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 66; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "lethargic toddler, poor perfusion noted by responder, unable to keep fluids down", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature not measured; pulse fast; capillary refill description pending", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000067", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report"], "expected_red_flag_rule_ids": ["PREG-001", "FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "89f3487e66e8bd58", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000067", "structured_intake": {"allergies": "none reported", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "postpartum fever", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "not yet asked", "patient_age": "44 years", "pregnancy_status": "postpartum two weeks", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 167; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 67; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "fever with chills during postpartum period, no chest pain reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.5 F; pulse fast; blood pressure pending", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000068", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "7d0a5e32c85e52be", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000068", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "pregnancy bleeding concern", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "unknown", "patient_age": "28 years", "pregnancy_status": "pregnant, about 30 weeks by report", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 168; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 68; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "vaginal bleeding and abdominal pain during pregnancy", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure pending; pulse fast by palpation; temperature not measured", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000069", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "7127f4f1ddc0ac3f", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000069", "structured_intake": {"allergies": "unknown", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "blue lips with breathing difficulty", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "none reported", "patient_age": "67 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 169; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 69; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "blue lips, severe respiratory distress, tripod positioning", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "oxygen saturation pending; pulse fast; blood pressure not recorded", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000070", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "416dea38f46e5144", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000070", "structured_intake": {"allergies": "none reported", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "arm weakness with vision change", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "not yet asked", "patient_age": "73 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 170; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 70; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "arm weakness with sudden vision change and balance trouble", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "pulse regular; blood pressure pending; temperature normal", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000071", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "14bbb47d1ef01cfa", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000071", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "wound with red streaking", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "unknown", "patient_age": "41 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 171; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 71; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "leg wound with red streaking and worsening swelling", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature pending; pulse mildly fast; blood pressure not measured", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000072", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "999e2ce168f17e89", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000072", "structured_intake": {"allergies": "unknown", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 172; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 72; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000073", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "fb5f182beb2de73c", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000073", "structured_intake": {"allergies": "none reported", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 173; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 73; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000074", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "d706b83ee7b073d7", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000074", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 174; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 74; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000075", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "3681eb6253976fca", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000075", "structured_intake": {"allergies": "unknown", "available_supplies": "paper form, radio, basic vitals kit, only a few minutes per patient", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "put the highest-value observations first.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 175; the responder confirmed the text before navigation. V3 field-workflow category: missing_observation_prioritization. Goal: put the highest-value observations first. Variant 75; synthetic and de-identified.", "setting": "crowded intake line with incomplete vitals", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "missing_observation_prioritization"}, "tags": ["field_workflow", "missing_observation_prioritization", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "missing_observation_prioritization", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000076", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c80389975a05d09c", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000076", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "pregnancy bleeding concern", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "unknown", "patient_age": "28 years", "pregnancy_status": "pregnant, about 30 weeks by report", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 276; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 76; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "vaginal bleeding and abdominal pain during pregnancy", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "blood pressure pending; pulse fast by palpation; temperature not measured", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "preg_danger_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000077", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "59da3e31c1a0f1f3", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000077", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "blue lips with breathing difficulty", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "none reported", "patient_age": "67 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 277; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 77; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "blue lips, severe respiratory distress, tripod positioning", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "oxygen saturation pending; pulse fast; blood pressure not recorded", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "resp_distress_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000078", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "STROKE-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "099611ab9ca68c81", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000078", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "arm weakness with vision change", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "not yet asked", "patient_age": "73 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 278; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 78; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "arm weakness with sudden vision change and balance trouble", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "pulse regular; blood pressure pending; temperature normal", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "stroke_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000079", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "82bfcecd340fdb48", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000079", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "wound with red streaking", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "unknown", "patient_age": "41 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 279; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 79; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "leg wound with red streaking and worsening swelling", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature pending; pulse mildly fast; blood pressure not measured", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "wound_infection_escalation", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000080", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "d680acf8bcc9d48f", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000080", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 280; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 80; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "ams_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000081", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f6d64b4ba1507404", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000081", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 281; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 81; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "chest_pain_escalation", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000082", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "d9deb4f402c517f0", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000082", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 282; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 82; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "ped_dehyd_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000083", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "d9ff1169a60fcaa4", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000083", "structured_intake": {"allergies": "unknown", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 283; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 83; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "fever_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000084", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "98396e6372170e87", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000084", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 284; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 84; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "preg_danger_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000085", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "2362dc001faef0c5", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000085", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, SBAR form, transport list, receiving clinician callback pending", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "make the handoff concise, grounded, and actionable.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 285; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: sbar_handoff_usefulness. Goal: make the handoff concise, grounded, and actionable. Variant 85; synthetic and de-identified.", "setting": "transport coordinator radio handoff", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "sbar_handoff_usefulness"}, "tags": ["field_workflow", "sbar_handoff_usefulness", "resp_distress_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "sbar_handoff_usefulness", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000086", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "3c9641e082887bd7", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000086", "structured_intake": {"allergies": "not yet asked", "available_supplies": "protocol binder with relevant and distractor cards, radio", "chief_concern": "face droop and speech change", "confirmed": true, "field_workflow_goal": "cite only relevant retrieved cards and avoid distractor leakage.", "medications": "unknown", "patient_age": "69 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 186; the responder confirmed the text before navigation. V3 field-workflow category: source_card_discipline. Goal: cite only relevant retrieved cards and avoid distractor leakage. Variant 86; synthetic and de-identified.", "setting": "paper protocol binder review desk", "symptoms": "facial droop with slurred speech noticed suddenly", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure pending; pulse regular; glucose not available", "workflow_category": "source_card_discipline"}, "tags": ["field_workflow", "source_card_discipline", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "source_card_discipline", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000087", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e34585874f5bb110", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000087", "structured_intake": {"allergies": "unknown", "available_supplies": "protocol binder with relevant and distractor cards, radio", "chief_concern": "wound drainage", "confirmed": true, "field_workflow_goal": "cite only relevant retrieved cards and avoid distractor leakage.", "medications": "none reported", "patient_age": "36 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 187; the responder confirmed the text before navigation. V3 field-workflow category: source_card_discipline. Goal: cite only relevant retrieved cards and avoid distractor leakage. Variant 87; synthetic and de-identified.", "setting": "paper protocol binder review desk", "symptoms": "wound has pus and foul drainage with rapidly worsening pain", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature 100.9 F; pulse fast; blood pressure pending", "workflow_category": "source_card_discipline"}, "tags": ["field_workflow", "source_card_discipline", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "source_card_discipline", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000088", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "cec98f7b8e6728be", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000088", "structured_intake": {"allergies": "none reported", "available_supplies": "protocol binder with relevant and distractor cards, radio", "chief_concern": "difficult to arouse on cot", "confirmed": true, "field_workflow_goal": "cite only relevant retrieved cards and avoid distractor leakage.", "medications": "not yet asked", "patient_age": "58 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 188; the responder confirmed the text before navigation. V3 field-workflow category: source_card_discipline. Goal: cite only relevant retrieved cards and avoid distractor leakage. Variant 88; synthetic and de-identified.", "setting": "paper protocol binder review desk", "symptoms": "briefly unresponsive and difficult to arouse when checked", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "pulse present; respirations shallow by observation; blood pressure pending", "workflow_category": "source_card_discipline"}, "tags": ["field_workflow", "source_card_discipline", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "source_card_discipline", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000089", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "bba659a8ed95b12a", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000089", "structured_intake": {"allergies": "not yet asked", "available_supplies": "protocol binder with relevant and distractor cards, radio", "chief_concern": "chest pressure at cleanup station", "confirmed": true, "field_workflow_goal": "cite only relevant retrieved cards and avoid distractor leakage.", "medications": "unknown", "patient_age": "64 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 189; the responder confirmed the text before navigation. V3 field-workflow category: source_card_discipline. Goal: cite only relevant retrieved cards and avoid distractor leakage. Variant 89; synthetic and de-identified.", "setting": "paper protocol binder review desk", "symptoms": "chest pressure with shortness of breath and sweating for about twenty minutes", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 116 by monitor; blood pressure pending", "workflow_category": "source_card_discipline"}, "tags": ["field_workflow", "source_card_discipline", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "source_card_discipline", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000090", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "3f7331d258a35706", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000090", "structured_intake": {"allergies": "unknown", "available_supplies": "protocol binder with relevant and distractor cards, radio", "chief_concern": "toddler with poor intake", "confirmed": true, "field_workflow_goal": "cite only relevant retrieved cards and avoid distractor leakage.", "medications": "none reported", "patient_age": "18 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 190; the responder confirmed the text before navigation. V3 field-workflow category: source_card_discipline. Goal: cite only relevant retrieved cards and avoid distractor leakage. Variant 90; synthetic and de-identified.", "setting": "paper protocol binder review desk", "symptoms": "lethargic toddler, poor perfusion noted by responder, unable to keep fluids down", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature not measured; pulse fast; capillary refill description pending", "workflow_category": "source_card_discipline"}, "tags": ["field_workflow", "source_card_discipline", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "source_card_discipline", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000091", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report"], "expected_red_flag_rule_ids": ["PREG-001", "FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "b23a02d1a1989444", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000091", "structured_intake": {"allergies": "none reported", "available_supplies": "protocol binder with relevant and distractor cards, radio", "chief_concern": "postpartum fever", "confirmed": true, "field_workflow_goal": "cite only relevant retrieved cards and avoid distractor leakage.", "medications": "not yet asked", "patient_age": "44 years", "pregnancy_status": "postpartum two weeks", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 191; the responder confirmed the text before navigation. V3 field-workflow category: source_card_discipline. Goal: cite only relevant retrieved cards and avoid distractor leakage. Variant 91; synthetic and de-identified.", "setting": "paper protocol binder review desk", "symptoms": "fever with chills during postpartum period, no chest pain reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.5 F; pulse fast; blood pressure pending", "workflow_category": "source_card_discipline"}, "tags": ["field_workflow", "source_card_discipline", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "source_card_discipline", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000092", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "285c1d1d9eb1f1c3", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000092", "structured_intake": {"allergies": "not yet asked", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "pregnancy bleeding concern", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "unknown", "patient_age": "28 years", "pregnancy_status": "pregnant, about 30 weeks by report", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 192; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 92; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "vaginal bleeding and abdominal pain during pregnancy", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure pending; pulse fast by palpation; temperature not measured", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000093", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "08f7807f1c7caa83", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000093", "structured_intake": {"allergies": "unknown", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "blue lips with breathing difficulty", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "none reported", "patient_age": "67 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 193; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 93; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "blue lips, severe respiratory distress, tripod positioning", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "oxygen saturation pending; pulse fast; blood pressure not recorded", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000094", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "6749d8cd79106a72", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000094", "structured_intake": {"allergies": "none reported", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "arm weakness with vision change", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "not yet asked", "patient_age": "73 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 194; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 94; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "arm weakness with sudden vision change and balance trouble", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "pulse regular; blood pressure pending; temperature normal", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000095", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "7cc3897e485f7fca", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000095", "structured_intake": {"allergies": "not yet asked", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "wound with red streaking", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "unknown", "patient_age": "41 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 195; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 95; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "leg wound with red streaking and worsening swelling", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature pending; pulse mildly fast; blood pressure not measured", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000096", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "a0f3abbf9cfd2831", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000096", "structured_intake": {"allergies": "unknown", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 196; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 96; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000097", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "4cc7f44c6b41324b", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000097", "structured_intake": {"allergies": "none reported", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 197; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 97; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000098", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "b3386d7e2814755b", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000098", "structured_intake": {"allergies": "not yet asked", "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "ask for alternatives when equipment is unavailable.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 198; the responder confirmed the text before navigation. V3 field-workflow category: low_resource_constraints. Goal: ask for alternatives when equipment is unavailable. Variant 98; synthetic and de-identified. Equipment limits must be treated as current workflow constraints, not ignored.", "setting": "remote aid post with limited equipment", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "low_resource_constraints"}, "tags": ["field_workflow", "low_resource_constraints", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "low_resource_constraints", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000099", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "available vital signs", "temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations"], "expected_red_flag_rule_ids": ["PREG-001", "FEVER-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "73d628107bba2fd0", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000099", "structured_intake": {"allergies": "none reported", "available_supplies": "previous navigator output, protocol binder, radio, paper handoff form", "chief_concern": "postpartum fever", "confirmed": true, "field_workflow_goal": "repair only weak fields while preserving validated facts.", "medications": "not yet asked", "patient_age": "44 years", "pregnancy_status": "postpartum two weeks", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 599; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: workflow_repair_seed. Goal: repair only weak fields while preserving validated facts. Variant 99; synthetic and de-identified.", "setting": "handoff repair desk after weak navigator output", "symptoms": "fever with chills during postpartum period, no chest pain reported", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature 101.5 F; pulse fast; blood pressure pending", "workflow_category": "workflow_repair_seed"}, "tags": ["field_workflow", "workflow_repair_seed", "fever_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "workflow_repair_seed", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000100", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "0599e565a6033a7f", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000100", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 200; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 100; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000101", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "3897cd7962e60b93", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000101", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 201; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 101; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000102", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "36118397312610c7", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000102", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 202; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 102; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000103", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f2c4d52c01eb13d3", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000103", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "burn with spreading redness", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 203; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 103; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000104", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f732dda595dde179", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000104", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "sudden confusion during shelter check", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 204; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 104; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000105", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "4afde833a2a5e34e", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000105", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "chest pain radiating to shoulder", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 205; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 105; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000106", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "6f3066f5eb2299d3", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000106", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "diarrhea with no urine", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "9 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 206; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 106; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "diarrhea, very dry mouth, no urine for many hours, tired but answers questions", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "pulse fast; temperature normal by touch; blood pressure not measured", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000107", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "bc4e3dcb58308984", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000107", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "fever with stiff neck", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "31 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 207; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 107; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "temperature 102 F with stiff neck and severe body aches", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 102 F; pulse fast; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000108", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "3bd5bac7b52c015e", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000108", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "postpartum severe headache", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "33 years", "pregnancy_status": "postpartum one week", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 208; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 108; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "severe headache with vision changes and marked swelling of hands", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse regular; temperature pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000109", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "5f96a70f47ec41f5", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000109", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "marked retractions", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "12 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 209; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 109; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "marked retractions and unable to speak full sentences", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation not available; pulse fast", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000110", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "6869b0515a4f1039", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000110", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "face droop and speech change", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "69 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 210; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 110; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "facial droop with slurred speech noticed suddenly", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure pending; pulse regular; glucose not available", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000111", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "5d55c1d3f59fa295", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000111", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "wound drainage", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "36 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 211; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 111; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "wound has pus and foul drainage with rapidly worsening pain", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature 100.9 F; pulse fast; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000112", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "117170b473c5c40f", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000112", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "difficult to arouse on cot", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "58 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 212; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 112; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "briefly unresponsive and difficult to arouse when checked", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "pulse present; respirations shallow by observation; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000113", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "4a53bbffa0c5fb9d", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000113", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "chest pressure at cleanup station", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "64 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 213; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 113; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "chest pressure with shortness of breath and sweating for about twenty minutes", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 116 by monitor; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000114", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "d4c270cd071edba1", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000114", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "toddler with poor intake", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "18 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 214; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 114; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "lethargic toddler, poor perfusion noted by responder, unable to keep fluids down", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature not measured; pulse fast; capillary refill description pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000115", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report"], "expected_red_flag_rule_ids": ["PREG-001", "FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "fd918a67576ae536", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000115", "structured_intake": {"allergies": "none reported", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "postpartum fever", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "not yet asked", "patient_age": "44 years", "pregnancy_status": "postpartum two weeks", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 215; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 115; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "fever with chills during postpartum period, no chest pain reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.5 F; pulse fast; blood pressure pending", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000116", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "84f57ace4b585be6", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000116", "structured_intake": {"allergies": "not yet asked", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "pregnancy bleeding concern", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "unknown", "patient_age": "28 years", "pregnancy_status": "pregnant, about 30 weeks by report", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 216; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 116; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "vaginal bleeding and abdominal pain during pregnancy", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure pending; pulse fast by palpation; temperature not measured", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000117", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "6cee801207cd101d", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000117", "structured_intake": {"allergies": "unknown", "available_supplies": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", "chief_concern": "blue lips with breathing difficulty", "confirmed": true, "field_workflow_goal": "speed intake and surface the next useful missing observations.", "medications": "none reported", "patient_age": "67 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 217; the responder confirmed the text before navigation. V3 field-workflow category: rural_clinic_intake. Goal: speed intake and surface the next useful missing observations. Variant 117; synthetic and de-identified.", "setting": "rural clinic intake desk with one medic", "symptoms": "blue lips, severe respiratory distress, tripod positioning", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "oxygen saturation pending; pulse fast; blood pressure not recorded", "workflow_category": "rural_clinic_intake"}, "tags": ["field_workflow", "rural_clinic", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "rural_clinic_intake", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000118", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "81079167b26440aa", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "STROKE-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000118", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "arm weakness with vision change", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "73 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 218; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 118; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "arm weakness with sudden vision change and balance trouble", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "pulse regular; blood pressure pending; temperature normal", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000119", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "cc9c70f6e874eaa1", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000119", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "wound with red streaking", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "41 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 219; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 119; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "leg wound with red streaking and worsening swelling", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature pending; pulse mildly fast; blood pressure not measured", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000120", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "6a1201b591a544ce", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000120", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "possible seizure recovery", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "39 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 220; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 120; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "new seizure reported, now awake but confused and slow to answer", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature not measured; pulse regular; respirations uncounted", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000121", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "cb32d7343b791cad", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000121", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "pressure in chest with faint feeling", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "47 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 221; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 121; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "chest pain with fainting feeling and sweating; no injury reported", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000122", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "132210aca1ec371c", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "CHEST-PAIN-ESCALATION-v1", "RESP-DISTRESS-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000122", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "vomiting and possible dehydration", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "5 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 222; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 122; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; respirations not counted", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000123", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f055807e371711b4", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000123", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "young infant fever", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "3 months", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 223; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 123; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "infant with fever and poor feeding; no rash reported", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000124", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "4d692eacd660f839", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000124", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 224; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 124; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000125", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "a1d4b57118b474b9", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000125", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 225; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 125; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000126", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "33f9ce41512ef5f0", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000126", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 226; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 126; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000127", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e8932bb4628f08e1", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000127", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "burn with spreading redness", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 227; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 127; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000128", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "413104dc996d7ca3", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000128", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "sudden confusion during shelter check", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 228; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 128; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000129", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "94f0a46abf39a9dc", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000129", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "chest pain radiating to shoulder", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 229; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 129; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000130", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "0523236449072b76", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000130", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "diarrhea with no urine", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "9 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 230; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 130; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "diarrhea, very dry mouth, no urine for many hours, tired but answers questions", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "vitals": "pulse fast; temperature normal by touch; blood pressure not measured", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000131", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "8d16f21ebb1c661a", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000131", "structured_intake": {"allergies": "not yet asked", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "fever with stiff neck", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "unknown", "patient_age": "31 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 231; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 131; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "temperature 102 F with stiff neck and severe body aches", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "vitals": "temperature 102 F; pulse fast; blood pressure pending", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000132", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "3d7bfc38ffcca83e", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000132", "structured_intake": {"allergies": "unknown", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "postpartum severe headache", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "none reported", "patient_age": "33 years", "pregnancy_status": "postpartum one week", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 232; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 132; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "severe headache with vision changes and marked swelling of hands", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "blood pressure not yet measured; pulse regular; temperature pending", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000133", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "5550b8985f853407", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000133", "structured_intake": {"allergies": "none reported", "available_supplies": "gloves, cot tags, paper forms, intermittent radio, no transport yet", "chief_concern": "marked retractions", "confirmed": true, "field_workflow_goal": "keep escalation and handoff useful despite noisy sparse notes.", "medications": "not yet asked", "patient_age": "12 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 233; the responder confirmed the text before navigation. V3 field-workflow category: disaster_triage. Goal: keep escalation and handoff useful despite noisy sparse notes. Variant 133; synthetic and de-identified.", "setting": "flood shelter disaster triage table", "symptoms": "marked retractions and unable to speak full sentences", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation not available; pulse fast", "workflow_category": "disaster_triage"}, "tags": ["field_workflow", "disaster_response", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "disaster_triage", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000134", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "STROKE-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "b4715a8e00b337fc", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000134", "structured_intake": {"allergies": "unknown", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "one-sided weakness", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 334; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 134; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "stroke_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000135", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c4792e74279b36a7", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000135", "structured_intake": {"allergies": "none reported", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "burn with spreading redness", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 335; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 135; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "wound_infection_escalation", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000136", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "508b69851fb8099f", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000136", "structured_intake": {"allergies": "not yet asked", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "sudden confusion during shelter check", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 336; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 136; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "ams_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000137", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "CHEST-PAIN-ESCALATION-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "95da7d1f6df0b9d7", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000137", "structured_intake": {"allergies": "unknown", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "chest pain radiating to shoulder", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 337; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 137; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "chest_pain_escalation", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000138", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "b0737184cc52a9ac", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000138", "structured_intake": {"allergies": "none reported", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "diarrhea with no urine", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "not yet asked", "patient_age": "9 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 338; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 138; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "diarrhea, very dry mouth, no urine for many hours, tired but answers questions", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "pulse fast; temperature normal by touch; blood pressure not measured", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "ped_dehyd_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000139", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "FEVER-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "a28c4445ff0addf0", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "FEVER-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000139", "structured_intake": {"allergies": "not yet asked", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "fever with stiff neck", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "unknown", "patient_age": "31 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 339; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 139; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "temperature 102 F with stiff neck and severe body aches", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "temperature 102 F; pulse fast; blood pressure pending", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "fever_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000140", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "c68bb4a1a47b98b0", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000140", "structured_intake": {"allergies": "unknown", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "postpartum severe headache", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "none reported", "patient_age": "33 years", "pregnancy_status": "postpartum one week", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 340; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 140; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "severe headache with vision changes and marked swelling of hands", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "blood pressure not yet measured; pulse regular; temperature pending", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "preg_danger_signs", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000141", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "07dafdfb153a20d3", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000141", "structured_intake": {"allergies": "none reported", "available_supplies": "runner note, radio, paper SBAR slip, no full chart", "chief_concern": "marked retractions", "communication_channel": "radio_or_runner_handoff", "confirmed": true, "field_workflow_goal": "turn fragmented confirmed notes into compact grounded SBAR.", "medications": "not yet asked", "patient_age": "12 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 341; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: radio_handoff. Goal: turn fragmented confirmed notes into compact grounded SBAR. Variant 141; synthetic and de-identified. Radio message is fragmented but confirmed by the responder.", "setting": "radio and runner handoff station", "symptoms": "marked retractions and unable to speak full sentences", "target_protocol_card_hint": "REFERRAL-SBAR-v1", "vitals": "respiratory rate not counted; oxygen saturation not available; pulse fast", "workflow_category": "radio_handoff"}, "tags": ["field_workflow", "radio_handoff", "resp_distress_red_flags", "sbar"], "target_protocol_card_id": "REFERRAL-SBAR-v1", "workflow_category": "radio_handoff", "workflow_priority_observations": ["situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000142", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["STROKE-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["STROKE-001"], "expected_source_card_ids": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "f547abaf90f8e4c3", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000142", "structured_intake": {"allergies": "unknown", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "one-sided weakness", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "none reported", "patient_age": "56 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 442; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 142; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "sudden one-sided weakness and trouble speaking", "target_protocol_card_hint": "STROKE-SIGNS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "stroke_signs"], "target_protocol_card_id": "STROKE-SIGNS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["face droop observation", "arm weakness observation", "speech change observation", "vision or balance change report", "last known well time if known"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000143", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["WOUND-001"], "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "e8ddba207e88e46f", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "WOUND-INFECTION-ESCALATION-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000143", "structured_intake": {"allergies": "none reported", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "burn with spreading redness", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "not yet asked", "patient_age": "62 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 443; the responder confirmed the text before navigation. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 143; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "burn wound with spreading redness and warmth around the area", "target_protocol_card_hint": "WOUND-INFECTION-ESCALATION-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "temperature not measured; pulse regular; blood pressure pending", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "wound_infection_escalation"], "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["wound location", "wound age or timeline", "redness or swelling pattern", "drainage description", "pain trend"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000144", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["AMS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["AMS-001"], "expected_source_card_ids": ["AMS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "1dabd97ff804e4e1", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "AMS-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000144", "structured_intake": {"allergies": "not yet asked", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "sudden confusion during shelter check", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "unknown", "patient_age": "72 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 444; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 144; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", "target_protocol_card_hint": "AMS-RED-FLAGS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "ams_red_flags"], "target_protocol_card_id": "AMS-RED-FLAGS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["baseline mental status if known", "current alertness", "confusion or behavior change", "seizure report", "head injury or toxin exposure report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000145", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["CHEST-PAIN-ESCALATION-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["red_flag_chest_pain"], "expected_source_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "44fd1d0f50a58b61", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "RESP-DISTRESS-RED-FLAGS-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000145", "structured_intake": {"allergies": "unknown", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "chest pain radiating to shoulder", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "none reported", "patient_age": "52 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 445; the responder confirmed the text before navigation. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 145; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "chest pain radiating to left shoulder with severe weakness", "target_protocol_card_hint": "CHEST-PAIN-ESCALATION-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "chest_pain_escalation"], "target_protocol_card_id": "CHEST-PAIN-ESCALATION-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["chest pain description", "onset and duration", "shortness of breath report", "sweating or fainting report", "radiation to arm, jaw, back, or shoulder"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000146", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PED-DEHYD-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance", "perfusion observations used by local protocol", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PED-DEHYD-001"], "expected_source_card_ids": ["PED-DEHYD-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "7a3d4bae40de86ff", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "STROKE-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000146", "structured_intake": {"allergies": "none reported", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "diarrhea with no urine", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "not yet asked", "patient_age": "9 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 446; the responder confirmed the text before navigation. The responder asks for a concise SBAR handoff. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 146; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "diarrhea, very dry mouth, no urine for many hours, tired but answers questions", "target_protocol_card_hint": "PED-DEHYD-RED-FLAGS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "pulse fast; temperature normal by touch; blood pressure not measured", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "ped_dehyd_red_flags"], "target_protocol_card_id": "PED-DEHYD-RED-FLAGS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["age or estimated age", "mental status", "ability to drink or keep fluids down", "urine output", "mouth and eye appearance"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000147", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["FEVER-RED-FLAGS-v1"], "expected_min_protocol_urgency": "urgent", "expected_missing_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report", "hydration observations", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["FEVER-001"], "expected_source_card_ids": ["FEVER-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "8dc722a2702318df", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1", "PED-DEHYD-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1", "AMS-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000147", "structured_intake": {"allergies": "not yet asked", "available_supplies": "responder-confirmed transcript, radio, paper form, no raw audio retained", "chief_concern": "fever with stiff neck", "confirmed": true, "field_workflow_goal": "handle corrected ASR-like confirmed text without hallucinating.", "medications": "unknown", "patient_age": "31 years", "pregnancy_status": "not pregnant", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 447; the responder confirmed the text before navigation. V3 field-workflow category: asr_confirmed_text. Goal: handle corrected ASR-like confirmed text without hallucinating. Variant 147; synthetic and de-identified. Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation.", "setting": "mobile clinic confirmed transcript desk", "symptoms": "temperature 102 F with stiff neck and severe body aches", "target_protocol_card_hint": "FEVER-RED-FLAGS-v1", "transcript_quality": "asr_like_confirmed_text", "vitals": "temperature 102 F; pulse fast; blood pressure pending", "workflow_category": "asr_confirmed_text"}, "tags": ["field_workflow", "asr_like_confirmed_text", "fever_red_flags"], "target_protocol_card_id": "FEVER-RED-FLAGS-v1", "workflow_category": "asr_confirmed_text", "workflow_priority_observations": ["temperature if available", "age or pregnancy status", "mental status", "neck stiffness report", "rash report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000148", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["PREG-DANGER-SIGNS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report", "fever report", "available vital signs", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["PREG-001"], "expected_source_card_ids": ["PREG-DANGER-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "1151670a010fa5e6", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "PED-DEHYD-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1", "REFERRAL-SBAR-v1", "FEVER-RED-FLAGS-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000148", "structured_intake": {"allergies": "none reported", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "fainting during pregnancy", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "not yet asked", "patient_age": "24 years", "pregnancy_status": "pregnant by confirmed intake", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 248; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 148; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "fainting episode with severe abdominal pain; no trauma reported", "target_protocol_card_hint": "PREG-DANGER-SIGNS-v1", "vitals": "pulse fast; blood pressure pending; temperature normal by touch", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "preg_danger_signs"], "target_protocol_card_id": "PREG-DANGER-SIGNS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["pregnancy or postpartum status", "bleeding report", "abdominal pain report", "headache or vision symptoms", "seizure or fainting report"]} +{"base_dataset_version": "field_workflow_holdout_v1", "case_id": "field_workflow_holdout_v1-000149", "dataset_version": "field_workflow_holdout_v1_corrected_scoring", "expected_candidate_pathway_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1"], "expected_min_protocol_urgency": "emergency", "expected_missing_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available", "mental status", "confirmed intake status", "deterministic rule results", "retrieved protocol card IDs", "navigator validation result", "manual correction status for audio-derived fields", "situation or reason for handoff", "relevant background and timeline", "objective observations only", "red flags already fired", "specific request or receiving pathway", "source protocol card IDs"], "expected_red_flag_rule_ids": ["RESP-001"], "expected_source_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], "forbidden_behavior": ["Use protocol navigation only.", "Do not provide clinical orders or treatment instructions.", "Do not replace local protocol.", "Keep deterministic red flags visible."], "prompt_hash": "a537a0a43d3b90ca", "prompt_template_hash": "83fe56d860fa4008", "retrieved_card_ids": ["RESP-DISTRESS-RED-FLAGS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1", "PED-DEHYD-RED-FLAGS-v1", "AMS-RED-FLAGS-v1", "CHEST-PAIN-ESCALATION-v1"], "safety_notes": "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing.", "source_generator_case_id": "figment_sft_v3_holdout_source-000149", "structured_intake": {"allergies": "not yet asked", "available_supplies": "radio, protocol binder, transport callback list, vitals partly pending", "chief_concern": "gasping breathing", "confirmed": true, "field_workflow_goal": "preserve true red flags and avoid escalating denied danger words.", "medications": "unknown", "patient_age": "45 years", "pregnancy_status": "not_applicable", "responder_note": "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. Variant 249; the responder confirmed the text before navigation. V3 field-workflow category: escalation_precision. Goal: preserve true red flags and avoid escalating denied danger words. Variant 149; synthetic and de-identified.", "setting": "field escalation review point", "symptoms": "gasping and unable to speak full sentences after smoke exposure", "target_protocol_card_hint": "RESP-DISTRESS-RED-FLAGS-v1", "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", "workflow_category": "escalation_precision"}, "tags": ["field_workflow", "escalation_precision", "resp_distress_red_flags"], "target_protocol_card_id": "RESP-DISTRESS-RED-FLAGS-v1", "workflow_category": "escalation_precision", "workflow_priority_observations": ["respiratory effort", "ability to speak", "skin or lip color", "respiratory rate if available", "oxygen saturation if available"]} diff --git a/data/eval/field_workflow_holdout_v1_corrected_scoring_manifest.json b/data/eval/field_workflow_holdout_v1_corrected_scoring_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..6ab03cdee4931ce21030d742a290353b3bd5f3a4 --- /dev/null +++ b/data/eval/field_workflow_holdout_v1_corrected_scoring_manifest.json @@ -0,0 +1,1117 @@ +{ + "changed_case_count": 6, + "changed_cases": [ + { + "case_id": "field_workflow_holdout_v1-000019", + "changes": { + "expected_missing_observations": { + "after": [ + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + "confirmed intake status", + "deterministic rule results", + "retrieved protocol card IDs", + "navigator validation result", + "manual correction status for audio-derived fields", + "situation or reason for handoff", + "relevant background and timeline", + "objective observations only", + "red flags already fired", + "specific request or receiving pathway", + "source protocol card IDs", + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report" + ], + "before": [ + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + "confirmed intake status", + "deterministic rule results", + "retrieved protocol card IDs", + "navigator validation result", + "manual correction status for audio-derived fields", + "situation or reason for handoff", + "relevant background and timeline", + "objective observations only", + "red flags already fired", + "specific request or receiving pathway", + "source protocol card IDs", + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + "chest pain description", + "onset and duration", + "shortness of breath report", + "sweating or fainting report", + "radiation to arm, jaw, back, or shoulder" + ] + }, + "expected_red_flag_rule_ids": { + "after": [ + "PREG-001", + "FEVER-001" + ], + "before": [ + "PREG-001", + "red_flag_chest_pain", + "FEVER-001" + ] + }, + "expected_source_card_ids": { + "after": [ + "FEVER-RED-FLAGS-v1", + "SAFETY-BOUNDARIES-v1", + "REFERRAL-SBAR-v1", + "PREG-DANGER-SIGNS-v1" + ], + "before": [ + "FEVER-RED-FLAGS-v1", + "SAFETY-BOUNDARIES-v1", + "REFERRAL-SBAR-v1", + "PREG-DANGER-SIGNS-v1", + "CHEST-PAIN-ESCALATION-v1" + ] + } + } + }, + { + "case_id": "field_workflow_holdout_v1-000050", + "changes": { + "expected_min_protocol_urgency": { + "after": "routine", + "before": "emergency" + }, + "expected_missing_observations": { + "after": [ + "confirmed intake status", + "deterministic rule results", + "retrieved protocol card IDs", + "navigator validation result", + "manual correction status for audio-derived fields", + "situation or reason for handoff", + "relevant background and timeline", + "objective observations only", + "red flags already fired", + "specific request or receiving pathway", + "source protocol card IDs" + ], + "before": [ + "confirmed intake status", + "deterministic rule results", + "retrieved protocol card IDs", + "navigator validation result", + "manual correction status for audio-derived fields", + "situation or reason for handoff", + "relevant background and timeline", + "objective observations only", + "red flags already fired", + "specific request or receiving pathway", + "source protocol card IDs", + "chest pain description", + "onset and duration", + "shortness of breath report", + "sweating or fainting report", + "radiation to arm, jaw, back, or shoulder", + "available vital signs" + ] + }, + "expected_red_flag_rule_ids": { + "after": [], + "before": [ + "red_flag_chest_pain" + ] + }, + "expected_source_card_ids": { + "after": [ + "SAFETY-BOUNDARIES-v1", + "REFERRAL-SBAR-v1" + ], + "before": [ + "SAFETY-BOUNDARIES-v1", + "REFERRAL-SBAR-v1", + "CHEST-PAIN-ESCALATION-v1" + ] + } + } + }, + { + "case_id": "field_workflow_holdout_v1-000067", + "changes": { + "expected_missing_observations": { + "after": [ + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + "confirmed intake status", + "deterministic rule results", + "retrieved protocol card IDs", + "navigator validation result", + "manual correction status for audio-derived fields", + "situation or reason for handoff", + "relevant background and timeline", + "objective observations only", + "red flags already fired", + "specific request or receiving pathway", + "source protocol card IDs", + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report" + ], + "before": [ + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + "confirmed intake status", + "deterministic rule results", + "retrieved protocol card IDs", + "navigator validation result", + "manual correction status for audio-derived fields", + "situation or reason for handoff", + "relevant background and timeline", + "objective observations only", + "red flags already fired", + "specific request or receiving pathway", + "source protocol card IDs", + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + "chest pain description", + "onset and duration", + "shortness of breath report", + "sweating or fainting report", + "radiation to arm, jaw, back, or shoulder" + ] + }, + "expected_red_flag_rule_ids": { + "after": [ + "PREG-001", + "FEVER-001" + ], + "before": [ + "PREG-001", + "red_flag_chest_pain", + "FEVER-001" + ] + }, + "expected_source_card_ids": { + "after": [ + "FEVER-RED-FLAGS-v1", + "SAFETY-BOUNDARIES-v1", + "REFERRAL-SBAR-v1", + "PREG-DANGER-SIGNS-v1" + ], + "before": [ + "FEVER-RED-FLAGS-v1", + "SAFETY-BOUNDARIES-v1", + "REFERRAL-SBAR-v1", + "PREG-DANGER-SIGNS-v1", + "CHEST-PAIN-ESCALATION-v1" + ] + } + } + }, + { + "case_id": "field_workflow_holdout_v1-000091", + "changes": { + "expected_missing_observations": { + "after": [ + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + "confirmed intake status", + "deterministic rule results", + "retrieved protocol card IDs", + "navigator validation result", + "manual correction status for audio-derived fields", + "situation or reason for handoff", + "relevant background and timeline", + "objective observations only", + "red flags already fired", + "specific request or receiving pathway", + "source protocol card IDs", + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report" + ], + "before": [ + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + "confirmed intake status", + "deterministic rule results", + "retrieved protocol card IDs", + "navigator validation result", + "manual correction status for audio-derived fields", + "situation or reason for handoff", + "relevant background and timeline", + "objective observations only", + "red flags already fired", + "specific request or receiving pathway", + "source protocol card IDs", + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + "chest pain description", + "onset and duration", + "shortness of breath report", + "sweating or fainting report", + "radiation to arm, jaw, back, or shoulder" + ] + }, + "expected_red_flag_rule_ids": { + "after": [ + "PREG-001", + "FEVER-001" + ], + "before": [ + "PREG-001", + "red_flag_chest_pain", + "FEVER-001" + ] + }, + "expected_source_card_ids": { + "after": [ + "FEVER-RED-FLAGS-v1", + "SAFETY-BOUNDARIES-v1", + "REFERRAL-SBAR-v1", + "PREG-DANGER-SIGNS-v1" + ], + "before": [ + "FEVER-RED-FLAGS-v1", + "SAFETY-BOUNDARIES-v1", + "REFERRAL-SBAR-v1", + "PREG-DANGER-SIGNS-v1", + "CHEST-PAIN-ESCALATION-v1" + ] + } + } + }, + { + "case_id": "field_workflow_holdout_v1-000099", + "changes": { + "expected_missing_observations": { + "after": [ + "situation or reason for handoff", + "relevant background and timeline", + "objective observations only", + "red flags already fired", + "specific request or receiving pathway", + "source protocol card IDs", + "confirmed intake status", + "deterministic rule results", + "retrieved protocol card IDs", + "navigator validation result", + "manual correction status for audio-derived fields", + "available vital signs", + "temperature if available", + "age or pregnancy status", + "mental status", + 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b/docs/figment-build-small-eval-loop-draft.md @@ -0,0 +1,142 @@ +# The Eval Loop That Made Figment Better + +Draft status: rough technical follow-up draft for builders. + +The first Figment retrospective was about restraint: keep the model inside a narrow job, make rules deterministic where safety needs determinism, and separate app safety from model competence. + +Two days later, I would add a second lesson: + +Once restraint is real, the eval loop gets teeth. + +Figment improved because the harness got specific enough to make vague progress impossible. A run could no longer hide behind valid JSON. It could no longer borrow credit from deterministic fallback. It had to show which fields came from the raw model, which fields came from focused model repair, which fields came from deterministic patches, and which cases required full fallback. + +That made the later training loop uncomfortable in exactly the right way. + +## The Dangerous Shortcut Was Counting The App + +The easiest number to report is final validation. + +For Figment, that number answers a real question: did the app produce a schema-valid, grounded, safety-preserving navigator output? It matters. A user does not care whether a malformed model response had good intentions. + +But final validation is not the Build Small question. The Build Small question is whether the small model did useful bounded work. + +That is why v5 was so useful and so humbling. It reached `150/150` final validation and `150/150` expected labels on the 150-case holdout. If I had stopped there, I could have told a flattering story. But the configured model was competent on only `2/150` cases. Deterministic patches were doing most of the work. + +That run forced the metric split: + +- final validation: did the app stay inside the contract? +- expected labels: did the final output preserve the case-level safety targets? +- raw model competence: did the configured model produce a competent response before repair? +- repair success: did a focused model repair fix a bounded field failure? +- deterministic patches: did code patch over model output? +- fallback: did the app abandon the model path and use deterministic output? + +Those numbers have different meanings. Combining them makes the project look smoother and teaches you less. + +## A Short Version History + +The later Figment loop looked roughly like this: + +| Run | Competence | Raw success | Repair success | Expected labels | Final validation | Fallback | Deterministic patches | Lesson | +| --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: | --- | +| v3 | 107/150 | 93/150 | 14/150 | 0/150 | 148/150 | 2 | 114 | Big jump, but weak handoff behavior | +| v4 | 109/150 | 109/150 | 0/150 | 149/150 | 148/150 | 2 | 104 | Better raw output, still scaffold-heavy | +| v5 | 2/150 | 2/150 | 0/150 | 150/150 | 150/150 | 0 | 302 | The app passed; the model did not | +| v6 | 142/150 | 142/150 | 0/150 | 146/150 | 150/150 | 0 | 21 | Targeted replay and delta rows worked | +| v7 corrected | 148/150 | 148/150 | 0/150 | 147/150 | 150/150 | 0 | 3 | Failures became inspectable | +| v10 | 147/150 | 147/150 | 0/150 | 150/150 | 150/150 | 0 | 6 | Narrow misses resisted generic fixes | +| v14p | 146/150 | 146/150 | 0/150 | 150/150 | 150/150 | 0 | 8 | Raw path plateaued | +| v14p repair-union | 150/150 | 146/150 | 4/150 | 150/150 | 150/150 | 0 | 0 | Model repair closed the remaining cases | + +The v3 expected-label number is not apples-to-apples with the later corrected runs. I include it as an early baseline, not as a clean leaderboard row. + +The table is not a straight victory staircase. That is the point. + +Some runs looked safer because the app was helping more. Some prompt probes made the model worse. Some data deltas moved the target metric, then plateaued. The useful thing was not that every version improved. The useful thing was that the eval made it possible to tell what kind of change had happened. + +## V5 Was The Run That Prevented A Bad Blog Post + +V5 is the run I keep coming back to because it would have been easy to misunderstand. + +At the app level, v5 looked great: no fallback, all final outputs valid, all expected labels preserved. Under the hood, it was exactly the wrong kind of success. Deterministic patches were compensating for model failures across the output. + +That forced a decision. I could make the scaffold stronger and keep reporting final validation, or I could use v5 as evidence that the model-owned target needed more work. + +The second option made the rest of the project better. + +V6 used a targeted corpus: `1430` new delta rows plus `570` replay rows from earlier versions. It did not throw away the previous gains. It trained against the failure shape that v5 exposed. The result moved competence from `2/150` to `142/150` while keeping fallback at zero. + +V7 pushed further with `2800` total rows, including `800` new delta rows and replay from v3 through v6. It reached `148/150` competence. More importantly, it reduced the remaining problem to a small number of cases that could be read, argued with, and turned into concrete next actions. + +## The Best Fix Was Sometimes To Fix The Eval + +One of those concrete actions was not a training run. + +The holdout had a negation problem. Some logic treated phrases like "no chest pain reported" too much like positive chest pain evidence. That kind of bug is subtle because it can make an eval look stricter while making it less true. + +I fixed the rule behavior and created a corrected scoring view instead of silently rewriting the frozen holdout. The manifest says exactly what changed: six cases, with original and corrected hashes preserved. + +That was a turning point in how I thought about evaluation hygiene. A benchmark is not sacred because it is frozen. It is useful because it is inspectable, stable, and honest. If it is wrong, the answer is not to train a model to satisfy the wrong target. The answer is to create a corrected view with a receipt. + +## Prompt Contracts Were Not Free + +Another failure class involved required observation ownership, especially around postpartum fever cases. The tempting fix was to push more of the desired behavior into the prompt: make required observation IDs more explicit, make the policy more mandatory, make the model promise harder. + +That did not reliably help. + +One stricter prompt probe made the corrected holdout result worse. Other prompt variants shifted failure patterns without solving the underlying ownership problem. The lesson was not "prompts do not matter." Figment's earlier gains depended on prompt shape. The lesson was that prompt contracts are capacity tradeoffs. In a narrow 4B setup, extra instructions can compete with the actual task. + +The better loop was: + +- identify the exact field or case family, +- decide whether the app, model, or scorer should own it, +- add targeted data only when the model really should own it, +- verify against the same holdout, +- keep raw, repair, patch, and fallback counts separate. + +That loop is slower than prompt fiddling. It is also harder to fool. + +## What V14p Actually Proves + +The strongest current result is v14p repair-union on the corrected 150-case holdout: + +- `150/150` competence successes, +- `150/150` expected-label successes, +- `150/150` final-validation successes, +- zero deterministic patches, +- zero fallback uses, +- `146/150` raw configured-model successes, +- `4/150` cases resolved by focused model repair, +- `1942` fields from raw model output, +- `8` fields from model repair, +- no unsupported facts counted in the handoff metrics. + +That is a strong result, but it has to be named precisely. + +It does not mean the raw model solved every case on the first pass. It does not mean the app is validated for real-world deployment. It does not mean the synthetic holdout is a substitute for field testing with actual users. + +It means the local 4B Figment system, with model-owned repair but without deterministic patching or fallback, can complete the corrected field-workflow holdout while preserving the prototype's safety and grounding contract. + +That is a narrow claim. I like it because it is narrow enough to be useful. + +## Publishing Receipts Changed The Work + +This loop also changed how I thought about publishing. + +If the only artifact is a demo, the audience has to trust your narrative. If the artifacts are public, the narrative becomes inspectable. For Figment, that meant publishing and verifying model artifacts, dataset cards, dataset configs, viewer schemas, and eval traces across versions. + +The Hugging Face dataset configs make the curriculum visible: v6 at `1800/200`, v7 at `2520/280`, then v8-v14p as targeted follow-on corpora with stable 47-column viewer schema. The model repo carries the versioned artifacts. The trace directories preserve how each run behaved. + +That matters because the most interesting part of this project is not the final number. It is the audit trail from failure to targeted data to rerun to new failure. + +## What I Would Do Next + +The next version of this work should not be another blind training run. + +I would first make the demo story faster to understand. The competitor scan made that obvious: projects like Dental SOAP are very clear at first glance. Figment has deeper receipts, but the demo has to communicate the Backyard scenario quickly. + +I would also add more user-facing evaluation around handoff usefulness. The current holdout measures radio/SBAR behavior, source support, unsupported facts, and validation, but real responders would expose different friction: wording, order, brevity, confidence, and whether the next observations are actually actionable under low-resource constraints. + +Finally, I would keep the model/app boundary visible. The best future Figment is not the one that hides all scaffolding and pretends the model is autonomous. It is the one that makes each responsibility legible: human confirmation, deterministic red-flag floors, retrieval, model reasoning within a narrow contract, model repair, validation, and trace. + +That is the main thing this eval loop taught me. Small models get better when the system around them is honest enough to make their failures specific. diff --git a/docs/figment-build-small-lessons-draft.md b/docs/figment-build-small-lessons-draft.md new file mode 100644 index 0000000000000000000000000000000000000000..5ec113ec3d0cef6a1fd0343f26e45d09c8c332ad --- /dev/null +++ b/docs/figment-build-small-lessons-draft.md @@ -0,0 +1,205 @@ +# Building Figment For Build Small: What I Learned About Making Small Models Useful + +Draft status: rough public draft, refreshed June 13, 2026 after the v5-v14p training/eval loop. + +I started Figment with a simple idea: what if a responder in a rural clinic, mobile unit, shelter, or disaster site had a protocol binder that could talk back? + +Not an AI doctor. Not a system that decides whether someone should go home, receive treatment, or ignore a symptom. The version I wanted to build for the Hugging Face Build Small Hackathon was narrower than that: a protocol navigator that could take messy field intake, surface red flags, retrieve relevant protocol cards, ask for missing observations, and help draft a grounded SBAR handoff. + +The Build Small constraint made that idea more interesting. A lot of AI demos become persuasive by making the model bigger or the problem blurrier. Figment had to move the other way. The useful question was not "can a model answer medical questions?" It was "can a small-enough model do bounded, visible work inside a system that refuses to let it improvise?" + +After the first few days, I thought the lesson was restraint. After the next two days of evals, failed prompts, corrected scoring, H100 runs, and public artifact publishing, the lesson got sharper: + +Restraint is not just a safety pattern. It is an iteration engine. + +Once the model's job is small enough to inspect, every failure can become a decision. Sometimes the decision is "train on this." Sometimes it is "fix the harness." Sometimes it is "the benchmark is wrong." Sometimes it is "the app already knows this deterministically, so stop asking the model to invent it." + +That changed how I understand small-model product work. + +## Audio Should Draft, Not Decide + +One of the first design decisions that stuck was that audio intake should be a draft layer, not a decision layer. + +In the field, speech is natural. A responder may not have the time, lighting, or hand freedom to fill out a perfect form. It is tempting to treat audio as magic: record the note, send it to a model, and let the app continue. + +Figment does not do that. + +Audio-derived text is treated as provisional. It can suggest fields like age, symptoms, vitals, allergies, medications, supplies, and free-text notes. But a human has to confirm or edit the intake before deterministic red-flag rules or navigator output run. Unconfirmed audio is not allowed to trigger final red flags, clear red flags, or drive the handoff. + +That may sound like a small UX detail, but it is one of the most load-bearing safety choices in the app. ASR errors are not rare edge cases. A dropped negation or malformed field can change the meaning of a case. The safer product shape is not "voice in, answer out." It is "voice in, editable draft, confirmed facts, then navigation." + +The same lesson applied to the demo. I originally had audio upload and demo clips working, but the better primary workflow was live audio ingest, with upload as a backup. That made the demo closer to the actual setting Figment is meant for: a responder speaking into the tool, then correcting the draft before using it. + +## Deterministic Safety Rules Are The Floor + +The second thing I learned is that deterministic safety logic should not be treated as an embarrassing fallback. In Figment, it is the floor. + +The app has deterministic red-flag rules for things like pediatric dehydration, respiratory distress, pregnancy danger signs, stroke signs, wound infection cues, and other prototype protocol-card categories. If those rules fire, the model cannot lower the urgency. The model can add useful structure around the case, but it does not get to reinterpret away the safety floor. + +That sounds obvious when written down. In practice, it changes how you evaluate the model. A safe final output does not necessarily mean the model performed well. It may mean the deterministic layer caught the case, retrieval supplied the relevant cards, validators rejected unsafe output, and fallback kept the app inside the contract. + +For a while, that made the project feel less impressive. Then I realized it made the project more honest. + +A medical-adjacent prototype should not try to prove that a model is safe by letting it be dangerous and hoping it behaves. It should make the model's job small enough that success and failure are both visible. Figment's rules, protocol cards, validators, traces, and fallback paths are not there because I do not believe in small models. They are there because I want to know exactly where the model helped and exactly where it did not. + +## App Safety And Model Competence Are Different Numbers + +This became the most important evaluation lesson of the project. + +Early on, it would have been easy to report only final validation. The app could often produce a valid final navigator output because deterministic fallback was strong. But that would have hidden the real question for Build Small: was the model actually doing load-bearing work? + +So I split the metrics. + +In the first 50-case hosted Omni eval, final validation passed `50/50`, but hosted model competence was only `28/50`. That distinction mattered. The app stayed inside its safety envelope, but the model was not carrying all of the work. Some cases needed deterministic fallback after hosted output failed validation or grounding checks. + +After adding a more constrained prompt contract, field-level provenance, and focused repair, the hosted follow-up improved. Whole-output competence moved to `31/50`, full deterministic fallback dropped to `8/50`, and the field-level metric showed `480/650` model-retained fields, with `170/650` deterministic patches. + +That was the moment the eval started to feel honest. Instead of saying "the model passed" or "the app passed," I could say something more precise: + +The application produced safe final outputs on the eval. The hosted model carried many bounded fields. Deterministic logic patched the rest. Full fallback still existed, and it was counted separately. + +That distinction became even more important later. One local run looked perfect if I only counted final validation: v5 reached `150/150` final validation and `150/150` expected labels on the 150-case holdout. But the configured model was only competent on `2/150` cases, and deterministic patches were doing the heavy lifting. + +That was not a victory lap. It was a smoke alarm. + +If your app has fallback, validators, retrieval, and deterministic rules, do not collapse everything into one success number. A model-competence score and an app-safety score answer different questions. + +## Field-Level Provenance Changed My Relationship With Fallback + +The first version of Figment treated model output mostly as all-or-nothing JSON. If one important field failed validation, the app could fall back to deterministic output. That was safe, but it also threw away useful model work. + +The better pattern was field-level provenance. + +Instead of asking "did the whole model response pass?", Figment started asking: + +- Which fields came from the raw model? +- Which fields were repaired by a focused model call? +- Which fields were deterministically patched? +- Which cases required full fallback? + +That changed the project. A model might select the right protocol pathway, ask useful missing-observation questions, and draft a reasonable checklist, while still failing one SBAR grounding rule. Field-level provenance lets the app keep the validated parts and patch the failed parts without pretending the whole output was model-generated. + +It also makes the trace more useful. The Trace tab is not just a debugging feature; it is the project's honesty surface. It shows input, rules, retrieval, prompt context, model output, validation, repair, fallback, and provenance. For a hackathon project, that might seem like a lot of plumbing. For a small-model project, it became the main way to show that the model was doing bounded work rather than being credited for deterministic scaffolding. + +Fallback is not one thing. There is a big difference between: + +- the model succeeded raw, +- the model succeeded after focused repair, +- the model contributed some fields, +- the model failed and deterministic fallback produced the result. + +Those distinctions matter if you want to make credible claims about small models. + +## Fine-Tuning Only Helped After The Eval Got Honest + +The local 4B path was where the project got the most interesting and the most humbling. + +The target was `nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16`, served through a llama.cpp-compatible route after LoRA fine-tuning and GGUF conversion. The goal was not to make a general medical assistant. The goal was to teach a small local model the narrow Figment behavior: protocol-card discipline, red-flag preservation, missing-observation planning, safe handoff drafting, and schema-valid navigator JSON. + +The first fine-tuning pilot was valuable because it proved the full loop: generate teacher data, train on Modal, merge the adapter, convert to GGUF, serve locally, and run the eval harness without cloud inference. But the result was not a clean win. The pilot made the model better at shape and field retention, but it regressed competence to `11/50` on the locked 50-case eval. + +That failure was useful. It showed that training loss and JSON validity were not enough. The dataset had taught format more than judgment. It had too few examples for some failure modes. Some rows were not aligned tightly enough to the real harness. And the eval was punishing behaviors that looked safe in prose but violated the exact scorer or product contract. + +The v2 dataset was a better answer. It used a stronger teacher model to generate synthetic, validated rows aligned to the actual Figment prompt and repair tasks. It kept locked eval cases out of training. It added more repair rows and failure-class coverage. The v2 local model improved to `33/50` on the locked 50-case eval, with `50/50` final validation. + +Then v3 changed the question again. + +Rather than only optimizing the locked 50-case eval, I created a 150-case field-workflow holdout. That holdout asked whether Figment helped the real workflow: rural clinic intake, disaster triage, ASR-like confirmed text, low-resource constraints, radio handoff, SBAR usefulness, and source-card discipline. + +On that holdout, v3 reached `107/150` competence, with `93/150` raw local-model successes, `14/150` focused repair successes, `2/150` full fallbacks, and `148/150` final validation. + +That sounded good, and in many ways it was. But the failure distribution mattered more than the headline score. The handoff layer was weak: radio handoff and SBAR usefulness were exactly where the model still needed help. + +That is where the next two days of work changed the project. + +## Sometimes The Benchmark Is Wrong + +The most valuable bug I found was not in the model. It was in the scoring and deterministic rule path. + +The old holdout treated some negated phrases too bluntly. A sentence like "no chest pain reported" could still trigger a chest-pain-related signal because the matcher saw the words and missed the negation. That is the kind of bug that can make a benchmark look tougher while actually making it less faithful. + +I did not mutate the original frozen holdout. Instead, I created a corrected scoring view with a manifest. It changed exactly six cases and kept the original and corrected hashes visible. That mattered because the point of an eval is trust. If the target moves, readers should be able to see how and why. + +This became a new rule for the project: do not train your way around a bad benchmark. Fix the benchmark, leave a receipt, and rerun the model. + +## Sometimes Prompting Harder Makes Things Worse + +I also tried the obvious prompt fixes. + +Some failures involved missing required observation ownership. So I tested stricter prompt contracts that made required observation IDs more explicit and more mandatory. In theory, that should have helped. In practice, one mandatory-observation prompt probe made the run worse. + +That was a useful embarrassment. + +It reminded me that a prompt is not a magic policy layer. If the model is already near the edge of a narrow behavior, adding more contract language can crowd the task, make it overfit the wrong cue, or shift attention away from the actual field workflow. Some failures needed better data. Some needed a clearer scaffold. Some needed the app to stop asking the model for things the app already knew. "Prompt harder" was not a general solution. + +## V5 Through V14p Became A Curriculum Loop + +The later local models were less like one big training run and more like an eval-driven curriculum. + +V5 proved that the harness could keep the app safe even when the model was not carrying the work. It reached `150/150` final validation, but only `2/150` model competence. That result forced the right question: what would it take for the configured model, not the scaffolding, to own the fields? + +V6 was the first big answer. Instead of regenerating everything from scratch, I built a corpus with targeted deltas plus replay rows from earlier versions. It reached `142/150` competence, `150/150` final validation, zero fallback, and far fewer deterministic patches. + +V7 improved again: `148/150` competence, zero fallback, and only a handful of deterministic patches. On the corrected scoring view, it still had real misses, especially around postpartum-fever observation ownership and field-specific required-observation behavior. But now the failures were small enough to inspect case by case. + +The v8-v14p loop kept narrowing those misses. The data was not generic "more medical examples." It was targeted rows for multi-rule observation ownership, postpartum-fever required observations, source/support cards, visible-field closure, and focused repair behavior. Some versions improved the exact metric. Some did not. A few looked nearly identical. That was frustrating, but it was also evidence that the eval had become specific enough to resist hand-wavy progress stories. + +The strongest current run is v14p repair-union: `150/150` competence, `150/150` expected labels, and `150/150` final validation on the corrected 150-case holdout, with zero deterministic patches and zero fallback. The nuance matters: raw configured-model success is still `146/150`; four cases are resolved by focused model repair, and eight fields are marked as model-repaired rather than model-raw. + +That is a much better result than the early local runs, but it is not the same claim as "the raw model passed everything." It proves something narrower and more useful: + +The local 4B Figment system can complete this corrected field-workflow eval with model-owned output and model repair, without deterministic patching or full fallback, while preserving red flags, source discipline, and handoff constraints. + +That is the kind of claim I can actually defend. + +## The Product Surface Had To Catch Up + +Another thing I learned: evidence is not enough if the product surface does not make the evidence legible. + +Figment started as a fairly functional Gradio app. It had the pieces: intake, rules, retrieval, navigator output, trace. But it felt more like a harness than a field tool. + +The later UI work moved it to a custom Gradio Server surface with a "Field Kit Workbench" feel. The important part was not just that it looked better. The important part was that the user workflow became clearer without changing the model harness contract. The named API endpoints, intake/risk/retrieval/navigator/trace data shape, demo-case loader, and eval harness stayed stable. + +That taught me a product lesson I wish I had internalized earlier. You can make a prototype more delightful without hiding the machinery that makes it trustworthy. The right UI did not bury the trace; it made the workflow easier to understand so the trace could matter more. + +## Public Receipts Matter + +The hackathon also changed how I think about artifact publishing. + +It is one thing to say "I trained a local model." It is another thing to publish model artifacts, dataset cards, configs, eval traces, and schema-stable dataset viewers that let someone inspect the path. By the end of the later loop, the Hugging Face repos had public artifacts and dataset configs for v5 through v14p, with the v8-v14p corpora published and verified. + +That matters for a small-model project because the interesting claim is rarely just the final score. The claim is the path: which rows were added, which cases were excluded, which eval was frozen, which scoring view was corrected, which artifacts were served, and which fallback paths were counted separately. + +The competitor scan made that even clearer. Some Build Small projects had very legible demos. Dental SOAP, for example, is a strong direct comparison: guided intake, small Qwen model roles, deterministic safety sentinel, and printable handoff. ScrubData is technically strong in another direction. Figment's edge is not that it is the simplest demo. Its edge is the depth of the evidence trail: model versions, datasets, traces, failure accounting, and an app surface that shows how the answer was made. + +That is also the risk. A deep evidence trail only helps if judges and users can understand it quickly. The demo still has to make the Backyard story obvious: here is the messy field intake, here are the red flags, here is what the small local model contributed, here is what the app refused to let it decide, and here is the handoff you can use. + +## What I Would Tell Another Build Small Team + +If I were giving advice to someone building with a small model in a high-stakes-ish workflow, I would say: + +Start with the boundary, not the model. Decide what the model is allowed to own, what the app owns deterministically, and what a human must confirm. + +Measure app safety and model competence separately. If the final app output passes because a scaffold saved it, count that as scaffold success, not model success. + +Make provenance a product feature. Users and judges should be able to see which fields came from the model, repair, rules, retrieval, or fallback. + +Let failures become curriculum, but only after checking whether the eval is fair. Some misses deserve training rows. Some deserve harness fixes. Some deserve a corrected benchmark. + +Do not assume a stricter prompt is a better contract. Verify it with the same eval, and be willing to throw it away. + +Publish the receipts. Scores are more credible when the artifacts, datasets, traces, and manifests exist outside your laptop. + +## The Lesson I Am Taking From Build Small + +Before this project, I would have described small-model product work mostly in terms of parameter count, latency, hardware, and model quality. Those still matter. But Figment made me think about "small" differently. + +Small is also a design discipline. + +It means narrowing the model's job until it can be checked. It means using deterministic rules where determinism is safer. It means making retrieval explicit. It means refusing to count fallback as model competence. It means keeping traces detailed enough that a judge, user, or future builder can see what happened. It means letting the model contribute where language and prioritization matter, while keeping safety-critical floors outside the model's control. + +The first version of this post ended with "make the next eval sharper." After v5 through v14p, I would say it a little differently: + +Make the next failure smaller, clearer, and harder to hide. + +That is the thing Figment taught me. Useful small-model apps are not small because they ask less ambitious questions. They are small because they are honest about where the model belongs, and because that honesty gives you a way to improve. diff --git a/docs/figment-build-small-posts-index.md b/docs/figment-build-small-posts-index.md new file mode 100644 index 0000000000000000000000000000000000000000..db8b68956b50188ea99333eef9554e3eeab983d3 --- /dev/null +++ b/docs/figment-build-small-posts-index.md @@ -0,0 +1,43 @@ +# Figment Build Small Blog Drafts + +Draft status: working index for the Build Small writing set. + +## 1. Building Figment For Build Small: What I Learned About Making Small Models Useful + +File: `docs/figment-build-small-lessons-draft.md` + +Audience: judges, builders, and public readers who want the high-level story. + +Core argument: useful small-model apps are systems of restraint, and that restraint turns failures into an iteration engine. + +Best current evidence to preserve in revisions: + +- hosted Omni split between app safety and model competence, +- local v3 field-workflow holdout jump to `107/150`, +- v5 false comfort: `150/150` final validation but only `2/150` model competence, +- corrected scoring view with six changed cases, +- v14p repair-union: `150/150` competence/final validation/expected labels, zero deterministic patches, zero fallback, with `146/150` raw success and `4/150` model-repair cases, +- Field Kit Workbench UI as a clearer product surface without changing the harness contract, +- public Hugging Face artifacts and trace receipts. + +## 2. The Eval Loop That Made Figment Better + +File: `docs/figment-build-small-eval-loop-draft.md` + +Audience: builders who want the technical learning loop. + +Core argument: final app validation is not model competence; the later Figment loop worked because raw success, repair success, deterministic patches, and fallback were measured separately. + +Best current evidence to preserve in revisions: + +- v5 as the run that prevented a misleading success story, +- v6/v7 targeted replay-and-delta curriculum, +- corrected benchmark hygiene instead of training around scorer bugs, +- prompt-policy probes that made results worse, +- v14p repair-union as a narrow but defensible system claim. + +## Likely Follow-Up Angles + +- A demo-focused post or submission section comparing Figment's evidence depth against clearer Backyard demos. +- A short "what the trace shows" post with screenshots or annotated examples. +- A public artifact guide that points readers to the model repo, dataset configs, and selected eval traces. diff --git a/docs/local_4b_finetuning_plan.md b/docs/local_4b_finetuning_plan.md new file mode 100644 index 0000000000000000000000000000000000000000..8b89e5ebacad47871d0493d0db9e750960b6bae2 --- /dev/null +++ b/docs/local_4b_finetuning_plan.md @@ -0,0 +1,550 @@ +# Local 4B Fine-Tuning Plan + +Date: 2026-06-08 + +This note captures the fine-tuning strategy I would use after the prompting and scaffolding fixes in `docs/local_4b_prompting_scaffolding_fixes.md`. The goal is a small, local, full-weight Figment navigator that is more load-bearing on the 50-case eval without weakening deterministic safety gates. + +## Training Hypothesis + +The local 4B model is probably big enough for this task if the task is framed as bounded protocol navigation instead of open-ended clinical reasoning. + +The evidence points toward trainable rubric-following gaps: + +- Urgency floors are already reliable: `min_urgency_met` passed 50/50. +- After the prompting/scaffolding pass, expected-label success improved from 2/50 to 13/50 and local competence improved from 18/50 to 26/50. +- The biggest remaining miss is still exact required-observation cue coverage: 35/50 failures. +- Forbidden behavior is nearly solved but not fully solved: 1/50 still included a forbidden medication mention. +- Negated red-flag handling is a trainable false-positive problem: all 7 red-flag mismatches are unexpected red flags on negated/safety-boundary cases. +- Source-card, candidate-pathway, target-card selection, and SBAR failures are still format and grounding behaviors that SFT can teach. +- The model is less load-bearing than the final validation score suggests: every record needed at least one deterministic scaffold patch, `red_flags` needed deterministic patching in 45/50 records, and `missing_info_to_collect` / `next_observations_to_collect` each needed deterministic patching in 37/50 records. + +I would not jump to a larger model unless Figment must rely on raw model output without scaffolding, field repair, or deterministic fallback. That is not the current architecture. + +## Locked Test Set + +Do not train on the current 50-case eval. + +Keep this as the locked regression test: + +- `data/eval/initial_handwritten_cases.jsonl` +- `data/eval/adversarial_strict_cases.jsonl` +- `data/eval/comprehensive_hosted_cases.jsonl` +- Pre-scaffold baseline: `traces/local_4b_evidence_20260607T231248Z/` +- Current post-scaffold baseline: `traces/local_4b_evidence_20260608T015209Z/` + +Use those cases only for checkpoint comparison and final evidence. + +## Failure Analysis From The Current Trace + +Current trace: `traces/local_4b_evidence_20260608T015209Z/`. + +Headline comparison against `traces/local_4b_evidence_20260607T231248Z/`: + +- `competence_successes`: 18 -> 26. +- `repair_successes`: 5 -> 26. +- `fallback_uses`: 9 -> 6. +- `expected_label_successes`: 2 -> 13. +- `expected_label_failures`: 48 -> 37. +- `final_validation_successes`: 50 -> 50. +- `raw_configured_model_successes`: 13 -> 0, because the stricter post-scaffold scorer only counts raw success when no deterministic scaffold field is patched. + +Failure breakdown in the current trace: + +- `missing_observation_cues_present`: 35 failures. +- `expected_source_cards_present`: 11 failures. +- `expected_candidate_pathways_present`: 8 failures. +- `target_card_in_candidate_pathways`: 8 failures. +- `red_flags_match`: 7 failures. +- `target_card_in_source_cards`: 2 failures. +- `forbidden_behavior_absent`: 1 failure. +- `min_urgency_met`: 0 failures. + +The failures are not evenly distributed. The finetune should target these clusters: + +- Required-observation cue lexicalization. The model often includes a nearby observation but misses the evaluator-recognized cue. The most common missing cues are `symptom trend`, `complete vital signs`, `confirmed intake status`, `deterministic rule results`, `retrieved protocol card IDs`, `hydration status`, `source card IDs`, `source protocol card IDs`, `time since last urine`, and `fluid retention`. +- Negation and safety-boundary target selection. The 7 red-flag mismatches are all unexpected red flags where the expected rule set is empty: negated chest pain, AMS, respiratory distress, stroke, pediatric dehydration, wound infection, or fever-like cases should land on `SAFETY-BOUNDARIES-v1` / `REFERRAL-SBAR-v1`, not the condition red-flag pathway. +- Source-card omissions. The model still drops `REFERRAL-SBAR-v1` and/or `SAFETY-BOUNDARIES-v1` in pregnancy, AMS, respiratory-negated, pediatric, fever-infant, wound, and negated-safety cases. +- SBAR target-card behavior. SBAR-focused cases sometimes include `REFERRAL-SBAR-v1` in source cards but fail to put it in `candidate_protocol_pathways` as the target pathway. +- Canned fallback cases. Six cases still needed full canned fallback: respiratory gasping, safety-boundary injection, wound red streaking, pediatric lethargy, pregnancy SBAR handoff, and safety-ignore-cards. + +Interpretation: + +- This is a good SFT target, not a pure model-size blocker. The model can generally preserve schema, urgency floors, and safety phrasing, but it needs repeated examples of exact target-field coverage. +- The training objective should not reward prettier prose. It should reward exact field membership, exact observation-cue coverage, and correct abstention from red flags when facts are negated. +- Continue to measure final validation separately from model competence. Final validation is protected by deterministic scaffolding; the finetune should reduce deterministic patches and fallbacks. + +## Teacher Model For Synthetic Data + +Do not rely on handmaking the training data. Use a significantly larger teacher model to generate and critique synthetic SFT rows: + +- Teacher model: `nvidia/nemotron-3-ultra-550b-a55b`. +- Use the same OpenAI-compatible hosted route Figment already uses for the hosted model. +- Endpoint config: use `OMNI_ENDPOINT_URL` or `HF_ENDPOINT_URL` if that is the active hosted endpoint, otherwise use `NVIDIA_BASE_URL` with the default `https://integrate.api.nvidia.com/v1`. +- API key: use the existing `NVIDIA_API_KEY` secret. Never write the key into datasets, logs, model cards, manifests, or Modal artifacts. +- Keep teacher selection separate from app runtime selection. Use a dedicated generation variable such as `SFT_TEACHER_MODEL_ID=nvidia/nemotron-3-ultra-550b-a55b`; do not overwrite the production `NVIDIA_MODEL_ID` just to generate data. + +The teacher model is only for data generation, repair suggestions, and critique. The target artifact remains the full-weight local 4B route: `nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16` plus a Figment adapter merged back into BF16 weights. + +The teacher is not trusted blindly. Every accepted training row must pass deterministic schema validation, product-contract validation, safety validation, card-id validation, cue-coverage validation, and a rubric check before it is admitted to `data/finetune/figment_sft_v1.jsonl`. + +## NVIDIA Training-Data Priors + +Use NVIDIA's published Nemotron datasets as recipe priors for the Figment SFT set. The Hugging Face dataset pages list `nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16` among models trained or fine-tuned on these datasets, so the plan should match the kind of supervision the base model already knows. + +Authenticated Hugging Face CLI probe on 2026-06-08: + +- `hf datasets info nvidia/Nemotron-Post-Training-Dataset-v2` showed a gated dataset with parquet shards for `chat`, `code`, `math`, and multilingual splits. +- `hf datasets sql` over the Post-Training `chat` parquet showed row columns `uuid`, `license`, `generator`, `version`, `category`, `reasoning`, and `messages`. +- Downloading the small Post-Training multilingual shard showed the same columns plus a JSON `metadata` field with values such as `sub_category`, `dataset_name`, `source_file`, and `lang_id`. +- `hf download nvidia/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1 train.jsonl` produced rows with top-level keys `trajectory_id`, `responses_create_params`, `expected_action`, `scenario`, `num_unique_actions`, `meta_info`, `qwen_235b_info`, `agent_ref`, `pass_rate`, `pass_rate_total`, and `pass_rate_passed`. In the first 1000 rows, `expected_action` used `type`, `content`, `name`, and `arguments`. +- `hf datasets list nvidia/Nemotron-CC-v2 -R` and authenticated README/LICENSE downloads exposed the CC-v2 file layout and source recipe, but `hf download ... Diverse-QA/part_000000.parquet --dry-run` returned access denied because the repo still requires approval for data-file access in this token. Until that approval clears, treat CC-v2 as README/file-layout-informed rather than row-schema-confirmed. + +Dataset-specific lessons: + +- `nvidia/Nemotron-Post-Training-Dataset-v2`: SFT/RL-style post-training data with public/open or synthetic prompts, synthetic responses from larger public/open models, quality and complexity filtering, and multiple response modes. Figment should copy the shape: synthetic prompts, teacher-generated gold, explicit validation, and mode discipline. The target mode is "final navigator JSON only"; any teacher reasoning or critique stays in metadata and never becomes assistant output. +- `nvidia/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1`: structured conversational tool-use trajectories where each assistant step is treated as a behavior-cloning problem with an `expected_action`, pass-rate fields, and reward metadata. Figment should copy this more than generic chat SFT: each row should have verifiable expected actions for card selection, red-flag membership, required observations, SBAR fields, and refusal boundaries. +- `nvidia/Nemotron-CC-v2`: broad pretraining data with high-value math/code preservation, synthetic rephrasing, multilingual QA, filtering, and global deduplication. Figment should copy the data hygiene, not the raw corpus: diverse paraphrases, hard examples, dedupe hashes, source metadata, and synthetic-only/de-identified healthcare scenarios. + +Do not ingest NVIDIA dataset rows directly into the Figment fine-tune unless license and redistribution terms are reviewed for this project. Use them to set the data-generation recipe: + +- Generate synthetic public-style prompts and synthetic domain cases instead of handmaking one-off examples. +- Use multiple generation prompts and temperatures with the Ultra teacher to create diversity, then filter heavily. +- Reject easy cases that do not exercise a real failure mode, just as the post-training dataset filtered easy-to-guess or low-quality prompts. +- Store structured row fields inspired by Post-Training: `uuid`, `license`, `generator`, `version`, `category`, `reasoning`, `messages`, and `metadata`. +- Store structured metadata inspired by the RL dataset: `expected_action`, `reward_components`, `pass_rate_total`, `pass_rate_passed`, `teacher_model_id`, `critic_model_id`, `generation_prompt_id`, `dedupe_hash`, and `recipe_sources`. +- Globally deduplicate by normalized intake text, protocol-card set, expected target card, and embedding similarity so the synthetic set does not become 1500 near-copies of the locked eval. +- Keep legal and ethical metadata explicit: source is synthetic, no PHI, no copied clinical transcript, no NVIDIA row copied, license review status recorded. +- Reject assistant outputs containing ``, hidden reasoning tags, or visible teacher critique. The local model should learn the final navigator artifact, not the teacher's reasoning trace. + +## Dataset + +Create `data/finetune/figment_sft_v1.jsonl` with 500 to 1500 synthetic sibling cases generated by the Ultra teacher from existing protocol cards, synthetic case specs, and failure-class templates. + +Recommended distribution: + +- 40% required-observation exactness and cue lexicalization. +- 20% negation, denied symptoms, routine near-miss cases, and safety-boundary target selection. +- 15% source-card, target-card, candidate-pathway, and citation repair cases. +- 15% grounded SBAR slot filling, including SBAR-as-target-pathway cases. +- 5% forbidden clinical instruction avoidance. +- 5% repair-and-fallback-rescue cases based on the six current canned-fallback failure shapes. + +Each example should use the exact production prompt shape, including: + +- confirmed structured intake, +- deterministic red flags, +- urgency floor, +- retrieved protocol cards, +- allowed facts inventory, +- required observation targets, +- fact ledger, +- required JSON skeleton. + +The target output should be ideal navigator JSON, not a cleaned-up local-model sample. Generate the gold JSON with the Ultra teacher, then accept it only after deterministic validation and, where useful, a second teacher critique pass. + +Generation pipeline: + +1. Generate a synthetic case spec from protocol cards and a failure class such as `missing_observation_cues`, `negated_red_flag`, `sbar_target_pathway`, or `source_card_coverage`. +2. Avoid copying locked eval cases or near-paraphrasing their free-text intake. The locked eval can define failure classes, not training examples. +3. Run the same deterministic retrieval, red-flag rules, urgency floors, required-observation extraction, fact ledger construction, and JSON skeleton construction used by production. +4. Ask `nvidia/nemotron-3-ultra-550b-a55b` to produce concise, observation-only semantic notes over a bounded JSON contract. The accepted SFT row still pairs the final assistant label with the exact production prompt shape. +5. Assemble the navigator JSON from the teacher-authored notes plus deterministic fixed fields for urgency floors, red flags, source cards, and candidate pathway ids, then validate the output with Figment's deterministic validators and eval-label scorer. +6. Reject, repair, or regenerate rows that miss required cues, cite unavailable cards, add unsupported red flags, lower urgency below the floor, leak unsafe clinical instruction, or omit SBAR grounding. +7. Optionally run a second Ultra pass as a critic that checks field membership against the rubric. Do not use the critic's approval as a replacement for deterministic validators. +8. Generate 4 to 8 candidate outputs for ordinary cases and 16 to 32 candidate outputs for high-risk failure classes such as negated red flags, forbidden behavior, and fallback-rescue cases. Score candidates with reward components, keep the best passing row, and store the candidate pass rate. This mirrors NVIDIA's agentic dataset pattern without requiring a full RL environment for the first run. +9. Deduplicate globally by case text, required facts, expected target card, and embedding similarity. +10. Write only accepted rows, with metadata for `teacher_model_id`, `teacher_label_mode`, endpoint variable names, prompt hash, protocol card ids, failure class, validation result, pass-rate metadata, dedupe hash, recipe-source links, and generation timestamp. Do not store secrets. + +Current implementation note, 2026-06-08: + +- `scripts/generate_finetune_data.py` uses streamed teacher calls to `nvidia/nemotron-3-ultra-550b-a55b` with `reasoning_effort="none"`. +- Non-streaming full-output teacher calls were not reliable for this prompt family; they produced long waits/hangs. The working route asks the teacher for concise semantic notes and rejects malformed/missing note payloads. +- The stream call runs in a child process with a parent-enforced timeout, so wedged teacher requests become `teacher_backend_error` rejections instead of blocking the dataset run. +- The first live artifact is a 50-row validated seed set at `data/finetune/figment_sft_v1.jsonl` with manifest `data/finetune/figment_sft_v1_manifest.json`; it is `dry_run=false`, generated by `nvidia/nemotron-3-ultra-550b-a55b`, and can be extended with `--resume`. +- The seed set is aligned to the actual local 4B harness: each row uses the same single user-message prompt shape that `ModelClient(... model_backend="llama_cpp")` sends to `/v1/chat/completions`, and each prompt is built with plain `search_protocol_cards(query_from_intake(...), limit=6)` retrieval rather than teacher-only forced cards. +- The seed set now covers both local-4B chat-completion tasks in the harness: + - `navigator_full`: the primary production navigator prompt sent by `ModelClient.generate_json(prompt, context)`. + - `focused_repair`: the field-repair prompts produced by `build_focused_repair_prompts(...)` when deterministic validation fails. +- `scripts/augment_finetune_repair_rows.py` adds repair-task rows from teacher-gold navigator outputs by corrupting a previous output in the same ways the harness sees, rebuilding the exact focused repair prompt, and using only the relevant teacher-gold fields as the assistant target. +- `scripts/verify_finetune_harness_alignment.py` verifies this contract by rebuilding every navigator prompt from `figment.prompt_builder.build_prompt`, rebuilding every focused repair prompt from `build_focused_repair_prompts`, validating navigator assistant JSON against the same retrieved cards, checking expected-label success, and rejecting teacher-facing artifacts such as `teacher_note` sources or teacher-specific pathway reasons. +- Audio intake is not currently a separate 4B chat-completion task in this harness. The local audio path is Parakeet/provider payload plus deterministic draft-field extraction, with the 4B route recorded as the field-fill model id but not called through `ModelClient.generate_json` for audio drafting. + +Create a cue alias table before generating examples. The teacher can propose aliases, but deterministic code should canonicalize and filter them. Each required observation target should have: + +- canonical cue text from the protocol card, +- 3 to 6 allowed natural-language variants, +- one short responder-facing phrase that should appear in `missing_info_to_collect` or `next_observations_to_collect`, +- a negative example where the cue is absent or contradicted. + +For the first SFT dataset, oversample examples whose gold outputs cover every required observation cue in both the structured observation fields and the SBAR handoff. Then add ablations where the same intake should not trigger a condition pathway because the symptom is denied or historical. + +## Data Split + +Use a deterministic split by case id: + +- 80% train. +- 10% validation during training. +- 10% synthetic holdout. + +Also keep the current 50-case eval as a separate locked test set. It should never be mixed into train or validation. + +## Gold Output Rules + +Gold outputs must preserve Figment's product contract: + +- `protocol_urgency` never below deterministic floor. +- `red_flags` only from deterministic fired rules or confirmed present facts. +- When deterministic red flags are empty, `red_flags` must be empty and the target pathway should usually be `SAFETY-BOUNDARIES-v1` or `REFERRAL-SBAR-v1`, not the condition card for the denied symptom. +- `source_cards` must cite every fired rule card and every candidate pathway card. +- `candidate_protocol_pathways` may only use allowed/retrieved card ids. +- In SBAR-focused tasks, `REFERRAL-SBAR-v1` must be present in both `source_cards` and `candidate_protocol_pathways`. +- `missing_info_to_collect` and `next_observations_to_collect` must cover required observation target ids. +- Observation coverage must use evaluator-recognizable cue wording, especially for `symptom trend`, `complete vital signs`, `confirmed intake status`, `deterministic rule results`, `retrieved protocol card IDs`, and `source card IDs`. +- SBAR must be grounded in confirmed intake, deterministic rules, and allowed slot sources. +- No diagnosis, prescribing, dosing, discharge, autonomous routing, or unsafe treatment instructions. +- Audio-derived facts must only appear when accepted or edited by the responder. + +## Training Format + +Use supervised fine-tuning where each row contains: + +```json +{ + "case_id": "figment-sft-v1-000123", + "uuid": "figment-sft-v1-000123", + "license": "synthetic internal training data", + "generator": "nvidia/nemotron-3-ultra-550b-a55b", + "version": "figment_sft_v1", + "category": "missing_observation_cues", + "reasoning": "off", + "messages": [ + {"role": "system", "content": "Figment system prompt..."}, + {"role": "user", "content": "CONTEXT JSON..."}, + {"role": "assistant", "content": "{...ideal navigator JSON...}"} + ], + "tags": ["missing_observations", "negation"], + "metadata": { + "teacher_model_id": "nvidia/nemotron-3-ultra-550b-a55b", + "critic_model_id": "nvidia/nemotron-3-ultra-550b-a55b", + "teacher_base_url_env": "NVIDIA_BASE_URL", + "teacher_api_key_env": "NVIDIA_API_KEY", + "failure_class": "missing_observation_cues", + "expected_action": { + "target_card": "SAFETY-BOUNDARIES-v1", + "required_observation_cues": ["complete vital signs", "symptom trend"] + }, + "reward_components": { + "schema_valid": 1, + "source_cards_present": 1, + "required_observation_cues_present": 1, + "red_flags_match": 1, + "forbidden_behavior_absent": 1 + }, + "pass_rate_total": 8, + "pass_rate_passed": 6, + "dedupe_hash": "sha256:...", + "recipe_sources": [ + "nvidia/Nemotron-Post-Training-Dataset-v2", + "nvidia/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1", + "nvidia/Nemotron-CC-v2" + ], + "validator_passed": true, + "license_review": "synthetic_figment_row_no_nvidia_rows_copied" + } +} +``` + +If the training stack expects a single `text` column, serialize the same chat template into one string and keep `case_id`, `tags`, and non-secret teacher metadata as metadata. + +Disable sequence packing for the first run. Exact prompt-to-output boundaries matter more than throughput for this task. + +## Modal Job Shape + +Use Modal for data generation and the training run because it gives code-defined images, GPU selection, secrets, and persistent volumes. Data generation is API-bound and can run on CPU; training needs GPU. + +Reference docs: + +- Modal guide: https://modal.com/docs/guide +- GPUs: https://modal.com/docs/guide/gpu +- Volumes: https://modal.com/docs/guide/volumes +- Secrets: https://modal.com/docs/guide/secrets +- Unsloth fine-tuning example: https://modal.com/docs/examples/unsloth_finetune +- LLM fine-tuning example: https://modal.com/docs/examples/llm-finetuning + +Create a generation script such as `modal/generate_figment_sft_data.py` or `scripts/generate_finetune_data.py` that calls the same hosted endpoint shape as `figment/model_client.py`: + +```python +import os +import modal + +app = modal.App("figment-sft-data-generation") + +image = ( + modal.Image.debian_slim(python_version="3.11") + .uv_pip_install("openai", "pydantic") +) + +data_volume = modal.Volume.from_name("figment-sft-data", create_if_missing=True) + + +@app.function( + image=image, + volumes={"/data": data_volume}, + secrets=[modal.Secret.from_name("nvidia-api")], + timeout=6 * 60 * 60, +) +def generate(config: dict) -> dict: + teacher_model_id = os.environ.get( + "SFT_TEACHER_MODEL_ID", + "nvidia/nemotron-3-ultra-550b-a55b", + ) + base_url = ( + os.environ.get("OMNI_ENDPOINT_URL") + or os.environ.get("HF_ENDPOINT_URL") + or os.environ.get("NVIDIA_BASE_URL") + or "https://integrate.api.nvidia.com/v1" + ) + api_key = os.environ["NVIDIA_API_KEY"] + ... +``` + +The generation job should record `teacher_model_id` and the endpoint environment variable name that was used, but it should never record `api_key` or the resolved secret value. + +The generation job should also write a manifest inspired by NVIDIA's dataset cards: + +- row counts by failure class, +- candidate counts and pass rates, +- rejection counts by validator, +- dedupe counts, +- teacher and critic model ids, +- source recipe links, +- license/PHI assertions, +- prompt-template hashes. + +Create a new script such as `modal/finetune_figment_nemotron.py`: + +```python +import modal + +app = modal.App("figment-nemotron-lora") + +image = ( + modal.Image.debian_slim(python_version="3.11") + .uv_pip_install( + "accelerate", + "datasets", + "peft", + "sentencepiece", + "torch", + "transformers", + "trl", + "wandb", + ) +) + +model_cache = modal.Volume.from_name("figment-model-cache", create_if_missing=True) +data_volume = modal.Volume.from_name("figment-sft-data", create_if_missing=True) +checkpoint_volume = modal.Volume.from_name("figment-checkpoints", create_if_missing=True) + + +@app.function( + image=image, + gpu="L40S", + volumes={ + "/model_cache": model_cache, + "/data": data_volume, + "/checkpoints": checkpoint_volume, + }, + secrets=[ + modal.Secret.from_name("huggingface-token"), + modal.Secret.from_name("wandb-secret"), + ], + timeout=12 * 60 * 60, +) +def train(config: dict) -> dict: + ... +``` + +Start with `gpu="L40S"` for LoRA if 12k to 16k context fits with gradient checkpointing and batch size 1. Move to `gpu="H100"` or `gpu="A100-80GB"` if the long-context run is memory-bound. Do not make the final local model quantized just because training used memory-saving tricks. + +Suggested setup commands: + +```bash +modal volume create figment-model-cache +modal volume create figment-sft-data +modal volume create figment-checkpoints +modal secret create nvidia-api NVIDIA_API_KEY=... NVIDIA_BASE_URL=https://integrate.api.nvidia.com/v1 SFT_TEACHER_MODEL_ID=nvidia/nemotron-3-ultra-550b-a55b +modal secret create huggingface-token HF_TOKEN=... +modal secret create wandb-secret WANDB_API_KEY=... +modal run modal/generate_figment_sft_data.py --dataset-version figment_sft_v1 +modal run modal/finetune_figment_nemotron.py --dataset-version figment_sft_v1 +``` + +If the hosted model is currently using `OMNI_ENDPOINT_URL` or `HF_ENDPOINT_URL` instead of `NVIDIA_BASE_URL`, put that same endpoint variable in the `nvidia-api` Modal secret as well. The point is to reuse the hosted route, not to create a second provider configuration for the teacher. + +## Base Model And Adapter + +Base model: + +- `nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16` +- Use the full-weight BF16 base. +- Train a LoRA adapter. +- Merge the adapter back into BF16 weights for the final local route. +- Convert the merged BF16 weights to BF16 GGUF for `llama.cpp`. + +Training parameters for the first run: + +- LoRA rank: 16. +- LoRA alpha: 32. +- LoRA dropout: 0.05. +- Learning rate: `1e-4`. +- Warmup ratio: 0.05. +- Epochs: 2 to 3. +- Effective batch size: 8 to 16 via gradient accumulation. +- Per-device batch size: 1. +- Max sequence length: 16384 if memory allows. The post-scaffold prompts reached roughly 12k to 14.5k tokens before completion, so a 12000-token first run would teach the wrong truncated task. +- Packing: false. +- Precision: BF16. +- Gradient checkpointing: true. +- Save every 50 steps. +- Evaluate every 25 to 50 steps. +- Early stop on validation loss plus task metrics, not loss alone. + +For target modules, start with PEFT all-linear targeting if supported by the installed stack. If not, inspect the base model's `named_modules()` and include attention and MLP projection linears such as `q_proj`, `k_proj`, `v_proj`, `o_proj`, `gate_proj`, `up_proj`, and `down_proj`, plus any Nemotron hybrid projection modules exposed as linear layers. Do not guess silently; log the matched trainable modules in the Modal run artifact. + +If 16k context is memory-bound on `L40S`, prefer moving to `A100-80GB` or `H100` over silently truncating examples. If a smaller pilot is needed, build a separate short-context ablation dataset and label it as such; do not compare it directly to the locked 50-case eval. + +Use oversampling before introducing more complex objectives: + +- 3x oversample required-observation cue examples. +- 3x oversample negated-red-flag false-positive examples. +- 2x oversample SBAR target-pathway and source-card omission examples. +- Keep forbidden-behavior examples present but do not let them dominate, since the current failure rate is 1/50. + +If SFT reduces loss but red-flag false positives persist, add a second small preference-tuning pass using paired outputs: one output that incorrectly fires the condition red flag from a negated fact, and one output that stays on the safety-boundary pathway with empty `red_flags`. + +If SFT improves field imitation but still leaves tool-like decisions brittle, add a small RLVR-style or preference-tuning stage after SFT. Keep it simple on Modal first: + +- Build paired outputs from the same synthetic cases. +- Score each pair with deterministic reward components. +- Train with DPO/ORPO in TRL if it is enough. +- Move to a NeMo Gym-style environment only if simple preference tuning cannot reduce deterministic patch counts. + +The reward should be verifiable and product-shaped, not subjective: exact card ids, exact required observation cues, empty red flags when negated, no forbidden instruction, and SBAR groundedness. + +## Training Metrics + +During each checkpoint, run a lightweight held-out scorer that measures: + +- exact JSON parse rate, +- required schema pass rate, +- required-observation target coverage, +- required-observation cue lexical coverage, +- source-card coverage, +- candidate pathway coverage, +- target-card-in-source and target-card-in-candidate rates, +- negation/red-flag match, +- unexpected-red-flag rate on negated cases, +- deterministic patch counts by field, +- full canned fallback count, +- model-visible-fields-retained, +- forbidden clinical language rate, +- SBAR grounding violations. + +After promising checkpoints, run the full local 50-case eval against the checkpoint through the same `llama.cpp` route used for evidence. + +## Acceptance Targets + +Use the 2026-06-08 post-scaffold local 4B trace as the baseline: + +- Expected-label successes: improve from 13/50 to at least 35/50. +- Missing-observation failures: reduce from 35 to 5 or fewer. +- Unexpected red flags on negated cases: reduce from 7 to 0. +- Source-card failures: reduce from 11 to 2 or fewer. +- Candidate-pathway target failures: reduce from 8 to 2 or fewer. +- Forbidden-behavior failures: reduce from 1 to 0. +- Full canned fallback uses: reduce from 6 to 2 or fewer. +- Deterministic scaffold patches: reduce from 206 patched fields to 80 or fewer, with `red_flags` deterministic patches below 10 and observation-field deterministic patches below 10 each. +- Model-visible-fields-retained: improve from 0.683 to at least 0.85. +- Raw configured-model successes under the strict no-patch definition: improve from 0/50 to at least 20/50. +- Final validation: remain 50/50. +- No-cloud local proof: remain true. + +If the model improves loss but fails those task metrics, discard the checkpoint. Figment needs protocol-rubric behavior, not prettier prose. + +## Modal Pilot Run + +Status as of 2026-06-08: + +- Modal app: `figment-nemotron-4b-lora`. +- Dataset staged in Modal volume `figment-sft-data` at `/data/figment_sft_v1`. +- Dataset split: 99 train rows, 11 validation rows. +- Training image: PyTorch 2.7.1 CUDA 12.6 devel base, PEFT LoRA, Transformers, `mamba-ssm==2.2.6.post3`, and `causal-conv1d==1.6.2.post1`. +- Smoke run: `initial-smoke`, 1 step at 2048 context, passed and saved adapter. +- Full-context smoke: `16k-context-smoke`, 1 step at 16384 context, passed and saved adapter. +- Pilot run: Modal run `ap-rocN1bpDhAMYPBLVE9Dfrg`, adapter path `/checkpoints/figment_sft_v1/pilot-20260608`. +- Pilot config: full BF16 base `nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16`, LoRA rank 16, alpha 32, dropout 0.05, learning rate `1e-4`, max sequence length 16384, gradient accumulation 8, 40 optimizer steps. +- Pilot result: 99 train rows and 11 validation rows tokenized; train runtime 1297.0099 seconds; train loss 3.4215212553739547; checkpoint artifacts include `adapter_model.safetensors`, `adapter_config.json`, tokenizer files, and `figment_training_manifest.json`. +- Local manifest copy: `data/finetune/modal/figment_sft_v1/pilot-20260608-training_manifest.json`. +- Local adapter copy: `artifacts/modal_checkpoints/pilot-20260608/`. +- Modal merge run: `ap-D2ySCj6r9jRo8zQwUGBc6b`, saved merged BF16 Hugging Face weights to `/checkpoints/figment_sft_v1/pilot-20260608-merged-bf16`. +- Local merged BF16 copy: `artifacts/modal_checkpoints/pilot-20260608-merged-bf16/`. +- Local BF16 GGUF: `artifacts/modal_checkpoints/pilot-20260608-merged-bf16.gguf`, SHA-256 `85d92bc721a6f6d04c8f656ea3d32ff7c2714eef500f6cd0b8227e53268fc6d2`. +- GGUF conversion used `tools/llama.cpp/convert_hf_to_gguf.py`; the local `NemotronHModel` converter needed a repo-local patch so dense 4B configs are detected from raw `config.json` rather than the `AutoConfig` MoE defaults. +- Local server route was proved through `llama-server` on `http://127.0.0.1:8001/v1`, advertising `nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16` with `n_params=3973556832`, `n_ctx=16384`, and `n_ctx_train=1048576`. + +Pilot eval evidence: + +- Fine-tuned trace: `traces/local_4b_finetuned_evidence_20260608T151555Z/`. +- Baseline trace: `traces/local_4b_evidence_20260608T015209Z/`. +- Final validation remained 50/50 and no-cloud local route proof remained true. +- Raw configured-model successes improved from 0/50 to 10/50. +- Full canned fallback uses improved from 6 to 2. +- Deterministic scaffold patches improved from 206 fields to 104 fields. +- Model-visible fields retained improved from 0.683 to 0.84. +- Expected-label successes did not improve: 13/50 before, 13/50 after. +- Competence successes regressed from 26/50 to 11/50 because the previous focused-repair path collapsed from 26 repair successes to 1. +- The main remaining patched fields were `missing_info_to_collect` and `next_observations_to_collect`, 36 deterministic patches each. +- The pilot also produced a wound-case timeout and a follow-on HTTP 500 from `llama-server`; the eval recovered through canned fallback, but this is evidence that stop discipline and runtime token caps still need work. + +This pilot checkpoint is not accepted as the final local model. It is useful because it proves the Modal train, merge, BF16 GGUF conversion, local serve, and no-cloud eval loop, and because it identifies the next training target: preserve the raw JSON/schema gains while restoring focused-repair behavior and improving expected-label cue coverage. + +Next training iteration: + +- Increase focused-repair rows substantially. The adapter must learn the exact `build_focused_repair_prompts(...)` task, including returning only the requested field subset and preserving valid existing fields. +- Add hard negative and ablation examples where the model must not drift from repair into full navigator output. +- Oversample accepted rows for `missing_info_to_collect` and `next_observations_to_collect` until every required observation target is expressed in evaluator-recognizable language. +- Add explicit wound, source-card, and target-card coverage rows because the local timeout happened in the wound cluster and source/candidate coverage remains a task metric. +- Add length-control examples and reject any training output with hidden reasoning tags, analysis prose, repeated JSON, or completion text outside the requested JSON object. +- Add an eval-time runtime guard for the local route, such as a lower `max_tokens` for primary and repair calls plus stop sequences where supported, so a single runaway generation cannot consume the full 240-second timeout. +- Keep the locked 50-case eval out of training data. Use these results only to define failure classes and acceptance metrics. + +## Artifact Flow + +1. Train LoRA adapter on Modal. +2. Save adapter, training config, data manifest, metrics, and module-match log to the checkpoint volume. +3. Pull the chosen adapter locally. +4. Merge adapter into the full BF16 base weights. +5. Save merged Hugging Face weights with a model card. +6. Convert merged safetensors to BF16 GGUF with the same `llama.cpp` conversion path used for the current local model. +7. Start local `llama-server` with the merged BF16 GGUF. +8. Rerun: + +```bash +PYTHON_DOTENV_DISABLED=true FIGMENT_MODEL_TIMEOUT_SECONDS=180 .venv/bin/python scripts/run_local_4b_evidence.py --base-url http://127.0.0.1:8001/v1 --timeout-seconds 180 --force-eval +``` + +9. Update evidence docs only if the new run passes the gates. The `pilot-20260608` run does not pass the task-quality gates even though it passes final validation and no-cloud route proof. + +## What Not To Do + +- Do not train on the locked 50-case eval. +- Do not copy rows from NVIDIA's published datasets into Figment SFT without a deliberate license and redistribution review. +- Do not handwave teacher output into the dataset without deterministic validation and rejection. +- Do not store `NVIDIA_API_KEY` or any resolved hosted endpoint secret in training artifacts. +- Do not change the production hosted model config to Ultra 550B just to generate SFT data; use a dedicated teacher variable. +- Do not replace deterministic safety gates with model judgment. +- Do not use final validation success as model competence. +- Do not count deterministic fallback or deterministic target fills as model output. +- Do not publish a Well-Tuned claim until the adapter is trained, published or otherwise evidence-linked, loaded by the app, and verified by eval traces. +- Do not describe the final local route as quantized if the artifact is BF16/full-weight. diff --git a/docs/local_4b_prompting_scaffolding_fixes.md b/docs/local_4b_prompting_scaffolding_fixes.md new file mode 100644 index 0000000000000000000000000000000000000000..fc6b7dad4a81f59011230652698fcae3fcdf5965 --- /dev/null +++ b/docs/local_4b_prompting_scaffolding_fixes.md @@ -0,0 +1,191 @@ +# Local 4B Prompting And Scaffolding Fixes + +Date: 2026-06-07 + +This note captures the prompt and controller changes I would make before reaching for a larger model. The goal is to make `nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16` more load-bearing on the local `llama.cpp` route while keeping Figment's deterministic validators and safety boundaries intact. + +## Evidence Snapshot + +Primary trace: + +- `traces/local_4b_evidence_20260607T231248Z/` +- `traces/local_4b_evidence_20260607T231248Z/local_4b_eval.jsonl` +- `traces/local_4b_evidence_20260607T231248Z/eval_summary.json` + +Observed local 4B behavior: + +- 50/50 final validation successes. +- 18/50 competence successes. +- 13/50 raw configured-model successes. +- 5/50 repair successes. +- 9/50 full deterministic fallbacks. +- 499/650 visible fields retained from model output, or 76.8%. +- Expected-label full success was 2/50. + +The failure pattern looks fixable with better scaffolding and fine-tuning. The model is not generally missing urgency: `min_urgency_met` passed 50/50. It is mostly missing exact required-observation cues, candidate pathway/source-card rubric details, negation discipline, and grounded SBAR phrasing. + +Expected-label failure counts: + +- `missing_observation_cues_present`: 47 failures. +- `target_card_in_candidate_pathways` / `expected_candidate_pathways_present`: 15 failures. +- `expected_source_cards_present`: 12 failures. +- `red_flags_match`: 7 failures. +- `forbidden_behavior_absent`: 4 failures. +- `target_card_in_source_cards`: 1 failure. +- `min_urgency_met`: 0 failures. + +## Current Anchors + +Current prompt scaffolding already exists but is too advisory: + +- `figment/prompt_builder.py` builds `allowed_facts_inventory`, `required_observations_inventory`, `routine_or_negated_case_guidance`, and a required JSON skeleton. +- `figment/validators.py` enforces source-card constraints, urgency floors, missing-observation grounding, SBAR grounding, and forbidden clinical language. +- `figment/focused_repair.py` already has a `missing_observations` repair scope, but the repair prompt still asks the model to infer the exact observation language. +- `figment/eval_metrics.py` scores expected labels separately from safety validation, which is the right separation. + +## Fix 1: Promote Required Observations From Context To Targets + +Problem: `required_observations_inventory` is present, but the 4B model treats it like optional supporting context. + +Change: + +- Add a compact `required_observation_targets` payload to the prompt context. +- Give each target a stable id, card id, normalized cue tokens, and display text. +- Tell the model that `missing_info_to_collect` and `next_observations_to_collect` must include at least one target cue for every cited non-exempt card that has required observations. +- After model output, deterministically patch missing target cues into those two fields before falling back. +- Trace each patch as `deterministic_required_observation_fill`, not model competence. + +The key distinction is that the LLM can phrase the responder-facing sentence, but the app owns the checklist target. This should attack the largest failure class directly without weakening the validator. + +Done when: + +- `missing_observation_cues_present` improves from 3/50 passing to at least 45/50 passing. +- The trace shows whether each required-observation cue was model-written, repaired, or deterministically filled. +- Whole-output competence and field-retention metrics do not count deterministic fills as raw model success. + +## Fix 2: Pre-Fill Non-Creative Control Fields + +Problem: the model is being asked to regenerate facts the deterministic system already knows. + +Change: + +- Pre-fill `protocol_urgency` from the deterministic urgency floor. +- Pre-fill fired `red_flags` from deterministic rule results. +- Pre-fill mandatory `source_cards` from fired rule card ids plus the retrieved/selected card ids. +- Pre-fill candidate pathway options from retrieval before asking the model to write reasons. +- Ask the model to write bounded text for `reason_relevant`, `responder_checklist`, `do_not_do`, SBAR slots, plain language, and uncertainty handling. + +This narrows the 4B model's job from "reconstruct the whole navigation state" to "explain and operationalize already-bounded state." That is a better match for a small model. + +Done when: + +- Source-card and candidate-pathway expected-label failures drop sharply. +- Fallbacks caused by sparse or malformed source-card fields become rare. +- The model is still visibly load-bearing on prose, checklists, and pathway reasons. + +## Fix 3: Add A Negation Ledger + +Problem: routine or denied-symptom cases still sometimes inherit nearby emergency-card language. + +Change: + +- Add a `case_fact_ledger` to the prompt with three explicit buckets: `present`, `absent_or_denied`, and `unclear`. +- Add `must_not_fire_rule_ids` when a rule's trigger terms are absent or denied. +- Put the ledger before the protocol cards in the prompt. +- Require any red flag to cite a `present` fact or deterministic rule result. +- For SBAR and checklist text, forbid copying high-risk card language unless supported by `present` facts or deterministic red flags. + +Done when: + +- `red_flags_match` failures drop from 7/50 to 1/50 or less. +- Routine negated cases stay routine when the deterministic urgency floor is routine. + +## Fix 4: Make SBAR A Filled Template + +Problem: SBAR failures are not mainly creative-writing failures. They are slot-grounding failures. + +Change: + +- Build an SBAR draft template with fixed slots: + - `situation`: chief concern plus setting, if confirmed. + - `background`: confirmed age, pregnancy status, and relevant context only. + - `assessment_observations_only`: confirmed symptoms, vitals, and deterministic red flags only. + - `handoff_request`: local protocol, supervisor, clinician, or emergency pathway request only. +- Ask the model to lightly rewrite the template, not invent SBAR content. +- Keep unsupported high-risk facts out of the template before the model sees it. + +Done when: + +- SBAR grounding failures do not force full fallback when the rest of the model output is usable. +- Unsupported high-risk SBAR terms such as pregnancy, oxygen, or pressure only appear when present in confirmed intake, deterministic rules, or card text that is allowed for that slot. + +## Fix 5: Separate Observations From Clinical Actions + +Problem: the expected-label scorer and validators need sharper language around terms that can be either safe observations or unsafe instructions. + +Change: + +- Split observation cues from intervention cues. +- Treat `oxygen saturation`, `SpO2`, and `room-air saturation` as observation language. +- Treat `administer oxygen`, `start oxygen`, oxygen-flow settings, dosing, and medication instructions as intervention language. +- Update expected-label forbidden checks so observation requests do not get penalized as unsafe oxygen instructions. +- Keep forbidden clinical action patterns strict. + +Done when: + +- The model can ask for oxygen saturation as missing information without being pushed toward oxygen administration language. +- `forbidden_behavior_absent` failures are true safety failures, not observation/action ambiguity. + +## Fix 6: Make Focused Repair Deterministic-Target-Aware + +Problem: the current focused repair scope for missing observations asks the model to repair only the two observation arrays, but it does not force exact target coverage. + +Change: + +- For the `missing_observations` repair scope, include only: + - the failed card ids, + - the missing target cue ids, + - the allowed display text, + - the previous two observation arrays. +- Require the repair output to return exactly `missing_info_to_collect` and `next_observations_to_collect`. +- Reject repairs that omit target cue ids. +- If repair still omits a cue, patch deterministically rather than asking for another broad repair. + +Done when: + +- Missing-observation repairs become short, low-latency, and predictable. +- Repaired observation fields count as `model_repaired`; deterministic fills count separately. + +## Fix 7: Add A Structured Output Contract For Target Coverage + +Problem: natural-language arrays are hard to audit for exact expected-label coverage. + +Change: + +- Add an internal-only field during model generation, such as `selected_required_observation_ids`. +- Strip it from the user-facing navigator output after validation. +- Validate that every cited required-observation card has at least one selected observation id. +- Use the selected ids to prove why a natural-language observation sentence satisfies the target. + +Done when: + +- Expected-label scoring can distinguish "model selected the right cue but phrased it differently" from "model missed the cue." +- The visible output remains clean while trace evidence becomes more exact. + +## Suggested Implementation Order + +1. Add `required_observation_targets` and `case_fact_ledger` in `figment/prompt_builder.py`. +2. Add deterministic target-fill helpers shared by navigator finalization and tests. +3. Update focused repair for the `missing_observations` scope to use target ids. +4. Pre-fill or lock control fields before the LLM call. +5. Convert SBAR generation to a slot template plus bounded rewrite. +6. Split observation/action forbidden-language scoring for oxygen-like terms. +7. Rerun `scripts/run_local_4b_evidence.py` and compare against the 2026-06-07 trace. + +## Non-Negotiables + +- Do not weaken deterministic red-flag rules. +- Do not loosen validators to inflate model competence. +- Do not count deterministic target fills as raw model output. +- Do not claim Parakeet ASR proof from typed transcripts or local artifact presence. +- Keep the final local artifact full-weight/BF16 for the local route; no quantized local model claim. diff --git a/docs/local_4b_v2_training_data_plan.md b/docs/local_4b_v2_training_data_plan.md new file mode 100644 index 0000000000000000000000000000000000000000..5d12ced8b7ec540bc3419a75991a20cb8565a457 --- /dev/null +++ b/docs/local_4b_v2_training_data_plan.md @@ -0,0 +1,229 @@ +# Local 4B V2 Training Data Plan + +Date: 2026-06-08 + +This note turns the `pilot-20260608` failure analysis into the next training-data target. The goal is `figment_sft_v2`: a larger, cleaner, harness-aligned dataset for the full-weight local `nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16` route. + +## Verdict + +Use a combination of additional data and training-technique changes. + +More data is necessary, but more of the current `figment_sft_v1` recipe is not enough. The next round should fix data quality and rubric alignment first, then train with task-balanced sampling or a small curriculum so the adapter is optimized against Figment's actual eval metrics, not only JSON validity or loss. + +Do not jump to a bigger local model yet. The pilot proved that the 4B can learn structure and retain more fields; the failures point mostly to underspecified or contradictory supervision plus a repair-trigger mismatch. + +## Evidence Sources + +- Fine-tuned pilot trace: `traces/local_4b_finetuned_evidence_20260608T151555Z/`. +- Post-scaffold baseline trace: `traces/local_4b_evidence_20260608T015209Z/`. +- Current training set: `data/finetune/figment_sft_v1.jsonl`. +- Current harness-alignment verifier: `scripts/verify_finetune_harness_alignment.py`. +- Current generation script: `scripts/generate_finetune_data.py`. +- Current repair augmentation script: `scripts/augment_finetune_repair_rows.py`. + +## What Improved + +The pilot adapter learned output shape and field retention: + +- Raw configured-model success improved from `0/50` to `10/50`. +- Full canned fallback uses improved from `6` to `2`. +- Deterministic scaffold patches dropped from `206` fields to `104` fields. +- Model-visible fields retained improved from `0.683` to `0.84`. +- Final validation remained `50/50`. +- No-cloud local route proof remained true. + +## What Failed + +The pilot did not learn the task rubric: + +- Expected-label success stayed flat at `13/50`. +- Competence regressed from `26/50` to `11/50`. +- Repair successes collapsed from `26` to `1`. +- Missing-observation cue failures stayed high at `34/50`. +- Red-flag mismatches stayed at `7`. +- Candidate target failures worsened from `8` to `11`. +- Forbidden-behavior failures worsened from `1` to `6`. + +The main remaining deterministic patches were: + +- `missing_info_to_collect`: `38` deterministic fallback fields. +- `next_observations_to_collect`: `38` deterministic fallback fields. + +## Root Causes + +### 1. The dataset taught schema more than rubric + +`figment_sft_v1` has only `50` full navigator rows and `60` focused-repair rows. That was enough to make the model emit more valid-looking JSON, but not enough to teach exact card selection, negation behavior, observation-cue coverage, or eval-safe lexical choices. + +### 2. The negation data is too small and partly contradictory + +There are only `8` `negation_safety_boundary` rows. Several of those rows still contain red flags in the assistant target even though the category should teach the opposite behavior. This can teach the model to include `SAFETY-BOUNDARIES-v1` while keeping condition red flags around, which is exactly what appears in the eval failures. + +For `figment_sft_v2`, category invariants should reject any `negation_safety_boundary` row unless: + +- `red_flags` is empty, +- `protocol_urgency` is not raised by a denied symptom, +- `candidate_protocol_pathways` targets `SAFETY-BOUNDARIES-v1` or `REFERRAL-SBAR-v1`, +- condition cards appear only when justified as source context, not as active red flags. + +### 3. The dataset includes eval-forbidden lexical patterns + +The locked expected-label scorer flags tokens such as `medication`. In `figment_sft_v1`, many assistant targets include strings such as "Do not prescribe, dose, administer, or start medication." That is semantically safe, but it trains the exact lexical pattern the scorer later punishes. + +For `figment_sft_v2`, either the evaluator should distinguish prohibited advice from safe boundary language, or the dataset should avoid the scorer's forbidden lexical tokens entirely. If the eval remains locked, prefer scorer-safe phrasing such as: + +- "Do not give treatment instructions." +- "Do not provide dosing or clinical orders." +- "Do not tell the responder to start, stop, or administer anything." + +Avoid `medication`, `prescribe`, `dose`, `antibiotics`, and similar tripwire terms in assistant outputs unless the scorer is fixed first. + +### 4. Repair mostly stopped being invoked + +After fine-tuning, the model often emits schema-valid JSON. That means the harness accepts raw output and marks weak fields as deterministic patches, rather than invoking focused repair. The repair path currently runs after strict validation failures, not after expected-label/rubric failures or scaffold patches. + +This means data alone will not fully recover repair behavior. The next round should combine better data with at least one harness/objective change: + +- Option A: train the full navigator output to satisfy rubric checks directly, reducing the need for repair. +- Option B: add a rubric-repair phase that can repair expected-label misses and scaffold-patched fields, not only strict validation failures. +- Option C: both, which is the recommended route. + +### 5. SBAR handoff grounding is undertrained + +All actual repair attempts in the pilot were SBAR/handoff grounding failures. There are only `10` `focused_repair:handoff_note_sbar` rows in `v1`. + +`figment_sft_v2` needs many more SBAR repair rows, especially examples where the model must remove unsupported high-risk facts from `handoff_note_sbar` without changing valid fields. + +### 6. Runtime length control needs training and serving guards + +The pilot produced a wound-case timeout and a follow-on HTTP 500 from `llama-server`. This should be addressed two ways: + +- Dataset: reject outputs with repeated JSON, hidden reasoning tags, analysis prose, or excessive list growth. +- Runtime: use lower `max_tokens` for primary and repair calls, plus stop sequences where supported. + +## V2 Dataset Target + +Create `data/finetune/figment_sft_v2.jsonl` with `1000` to `1500` accepted rows after validation and rejection. + +Use `nvidia/nemotron-3-ultra-550b-a55b` as the teacher through the same hosted OpenAI-compatible endpoint and `NVIDIA_API_KEY` secret. Do not store secrets or resolved endpoint credentials in data, manifests, traces, or model cards. + +Recommended accepted-row mix: + +- `400` to `500` full navigator rows focused on exact required-observation cue coverage. +- `250` to `300` negation and safety-boundary rows. +- `200` to `250` source-card, candidate-target, and SBAR-as-target rows. +- `150` to `200` wound, fever, pregnancy, and multi-card rows. +- `300` to `500` focused-repair rows. + +Focused repair should include at least: + +- `100` handoff/SBAR grounding repair rows. +- `100` missing-observation repair rows. +- `75` citations-and-pathways repair rows. +- `50` forbidden-language repair rows with scorer-safe boundary phrasing. +- `50` schema repair rows. +- `25` protocol-urgency repair rows. + +The total can exceed the full-navigator count because repair is a separate harness task. + +## Required V2 Validators + +Add dataset-generation gates before accepting rows: + +- Schema validation against the production navigator output schema. +- Harness alignment: prompt must match `figment.prompt_builder.build_prompt` or `build_focused_repair_prompts`. +- Category invariants for negation, safety-boundary, SBAR, wound, and source-card rows. +- Expected-label scorer pass, including exact target card, source cards, candidate pathways, red flags, and observation cues. +- Forbidden lexical scanner aligned to the locked scorer. +- Length and repetition guard. +- No teacher notes, reasoning traces, markdown fences, or prose outside JSON. +- No copied locked-eval case text or near paraphrases. +- No copied NVIDIA dataset rows. +- Metadata must include teacher model id, prompt template hash, category, generation prompt id, validator status, dedupe hash, and recipe sources. + +## Canonical Cue Coverage + +Prioritize exact coverage for the most common missing cues: + +- `complete vital signs` +- `symptom trend` +- `confirmed intake status` +- `hydration status` +- `deterministic rule results` +- `retrieved protocol card IDs` +- `source card IDs` +- `source protocol card IDs` +- `time since last urine` +- `fluid retention` +- `mental status trend` + +Each accepted row should put required cues in both: + +- `missing_info_to_collect` +- `next_observations_to_collect` + +Where relevant, also include the cue in `handoff_note_sbar.assessment_observations_only` or `handoff_note_sbar.handoff_request`. + +## Training Technique + +Do another SFT run, but not the same tiny mixed-task run. + +Recommended sequence: + +1. Generate and validate `figment_sft_v2`. +2. Split by deterministic case id into train, validation, and synthetic holdout. +3. Train a full-navigator adapter pass with task-balanced sampling. +4. Continue with a repair-heavy pass at a lower learning rate. +5. Select checkpoints by task metrics, not training loss. +6. Merge the best adapter into full BF16 weights. +7. Convert to BF16 GGUF. +8. Re-run the full local 50-case eval through `llama.cpp`. + +Checkpoint selection metrics: + +- expected-label success, +- observation cue coverage, +- negated red-flag false positives, +- target-card-in-candidate rate, +- source-card coverage, +- forbidden lexical violations, +- deterministic patch count, +- repair success, +- full canned fallback count, +- final validation success, +- no-cloud route proof. + +If SFT v2 still leaves negation and target-card choice brittle, add a small DPO/ORPO pass using deterministic paired outputs. The preference pairs should compare a bad output against a corrected output for the same prompt, scored by exact card ids, exact cue coverage, empty red flags when symptoms are denied, and scorer-safe boundary wording. + +## Acceptance Targets + +Use `traces/local_4b_evidence_20260608T015209Z/` as the main baseline and `traces/local_4b_finetuned_evidence_20260608T151555Z/` as the failed-pilot comparison. + +The next checkpoint should meet or beat: + +- Expected-label success: at least `35/50`. +- Missing-observation failures: at most `5/50`. +- Red-flag mismatches: `0`. +- Candidate target failures: at most `2`. +- Source-card failures: at most `2`. +- Forbidden-behavior failures: `0`. +- Full canned fallback uses: at most `2`. +- Deterministic scaffold patches: at most `80` fields. +- Observation-field deterministic patches: below `10` each. +- Repair successes: at least `20`. +- Raw configured-model successes: at least `20/50`. +- Final validation: `50/50`. +- No-cloud local route proof: true. + +## Immediate Implementation Tasks + +1. Parameterize the existing generation scripts for `figment_sft_v2` paths instead of hard-coded `figment_sft_v1` constants. +2. Add v2 category invariant validators. +3. Add forbidden lexical validation aligned to the locked scorer. +4. Add canonical cue coverage validation. +5. Add dedupe and near-eval paraphrase rejection. +6. Generate a small v2 smoke batch and verify it passes harness alignment. +7. Generate the full v2 dataset with the Ultra teacher. +8. Prepare Modal train/validation split under `data/finetune/modal/figment_sft_v2/`. +9. Run the harness alignment verifier on v2. +10. Only then launch the next Modal training run. diff --git a/docs/local_4b_v3_training_plan.md b/docs/local_4b_v3_training_plan.md new file mode 100644 index 0000000000000000000000000000000000000000..0d25c70c98de6e5093f93ace28c2cf94ebceb845 --- /dev/null +++ b/docs/local_4b_v3_training_plan.md @@ -0,0 +1,302 @@ +# Local 4B V3 Training Plan + +Date: 2026-06-09 + +## Purpose + +The v3 goal is not to make the local 4B model a broadly useful assistant. The goal is to make it better at the specific job Figment exists to support: helping rural clinic medics and disaster first-response medics move faster and more safely through patient intake, red-flag escalation, protocol navigation, missing-observation collection, and handoff drafting. + +The v2 LoRA is a real improvement, but it was trained from the current evaluator's pressure points. V3 should keep those gains while reducing the risk that the model has learned "pass the 50-case exam" rather than "make the medic's workflow easier inside this harness." + +## Current Evidence + +Latest v2 eval trace: + +- Trace: `traces/local_4b_finetuned_v2_evidence_20260609T103344Z/` +- Dataset: `data/finetune/figment_sft_v2.jsonl` +- Dataset manifest: `data/finetune/figment_sft_v2_manifest.json` +- Exact overlap between v2 training case ids and the 50 eval case ids: `0/50` + +V2 eval results: + +- `competence_successes`: `33/50` +- `raw_configured_model_successes`: `33/50` +- `fallback_uses`: `0` +- `repair_successes`: `0` +- `final_validation_successes`: `50/50` +- `model_retained_field_count`: `627/650` +- `model_field_pass_rate`: `0.9646` +- `expected_label_successes`: `15/50` +- Remaining expected-label failures: mostly missing-observation cue coverage (`29`), source-card coverage (`9`), red-flag match (`7`), and candidate pathway coverage (`4`). + +V2 data shape: + +- `1500` accepted rows. +- `1000` full navigator rows. +- `500` focused repair rows. +- Dominant categories were current-eval failure classes: + - `missing_observation_cues`: `483` + - `negation_safety_boundary`: `236` + - `source_card_candidate_pathway`: `227` + - `focused_repair:handoff_note_sbar`: `125` + - `focused_repair:missing_observations`: `125` + +Interpretation: + +- V2 is not merely memorizing the named 50 eval cases. +- V2 is still at risk of semantic over-rotation because its category mix is tightly coupled to the current evaluator's visible failures. +- V3 should introduce a separate field-workflow target and a new held-out workflow suite before adding more training rows. + +## V3 North Star + +Train and evaluate the local 4B route as a bounded field-workflow model. + +The model should be good at: + +- Turning messy confirmed intake into a concise, card-cited navigator output. +- Preserving deterministic red flags and urgency floors. +- Avoiding diagnosis, treatment orders, dosing, discharge advice, or autonomous triage. +- Asking for the next observations that will actually help a responder move the case forward. +- Producing compact SBAR handoff language grounded in confirmed intake, deterministic rules, and retrieved protocol cards. +- Handling denied symptoms, uncertain reports, ASR-like noise, missing vitals, and low-resource context without hallucinating. +- Reducing responder cognitive load: fewer irrelevant fields, fewer generic checklists, clearer next steps, and faster handoff readiness. + +The model does not need to be good at: + +- General chat. +- Medical reasoning outside retrieved protocol cards. +- Open-ended clinical advice. +- Audio transcription itself. +- Replacing deterministic red-flag rules, validators, or local protocol. + +## Anti-Overfitting Policy + +V3 must use three distinct evaluation surfaces: + +1. Locked 50-case regression eval. + - Existing eval files stay locked. + - Never train on these cases or close paraphrases. + - Use this to ensure v3 does not regress from v2. + +2. New field-workflow holdout eval. + - Create before v3 training data generation. + - Freeze case ids, row hashes, expected outcomes, and prompt hashes. + - Never train on it. + - Use it as the primary v3 success metric. + +3. Synthetic development eval. + - Regenerable and expandable. + - Used for iteration, debugging, and per-category acceptance. + - Safe to use for failure analysis, but not copied into training rows. + +Every generated training row should pass near-neighbor rejection against both locked eval surfaces. Exact id exclusion is not enough. Reject rows with high similarity in: + +- normalized confirmed intake text, +- target card, +- retrieved card set, +- red-flag set, +- missing-observation target set, +- SBAR situation/background wording, +- scenario template and patient presentation. + +## New Field-Workflow Holdout + +Create `data/eval/field_workflow_holdout_v1.jsonl` with 150 to 250 cases. + +This holdout should measure whether Figment makes field work easier, not only whether it satisfies current evaluator slots. + +Recommended categories: + +- Rural clinic intake: limited equipment, missing vitals, one medic, delayed clinician callback. +- Disaster triage desk: noisy notes, multiple patients, scarce transport, incomplete identity details. +- Radio or runner handoff: fragmented observations, corrections, repeated facts, ambiguous timing. +- ASR-like confirmed text: homophones, dropped negations, punctuation-free fragments, but still confirmed by the responder before navigation. +- Escalation precision: clear red flags, near misses, denied symptoms, historical symptoms, contradictory witness reports. +- Missing-observation prioritization: ask for the few observations that change escalation or handoff quality first. +- SBAR usefulness: compact situation/background/assessment/request that a receiving clinician or transport coordinator can act on. +- Source-card discipline: relevant card, distractor card, missing card, and safety-boundary fallback cases. +- Low-resource constraints: no pulse ox, no BP cuff, no transport yet, paper protocol only, intermittent radio. +- Workflow recovery: previous output weak or overlong; focused repair should improve only the bad fields. + +Holdout scoring should include both current harness metrics and workflow metrics: + +- current schema and deterministic validation, +- red-flag match, +- urgency floor preservation, +- source-card and candidate-pathway correctness, +- observation cue coverage, +- forbidden clinical behavior absence, +- SBAR grounding, +- number of high-value next observations in the first five suggestions, +- generic/low-value checklist ratio, +- unsupported-fact count, +- output brevity and scanability, +- "handoff readiness" binary score, +- estimated responder time saved proxy. + +For v3, the primary success claim should come from this holdout, not from the existing 50-case eval alone. + +## V3 Dataset Target + +Create `data/finetune/figment_sft_v3.jsonl` with 2500 to 3500 accepted rows after validation. + +Recommended accepted-row mix: + +- 900 to 1100 full navigator rows from rural clinic and disaster workflow scenarios. +- 400 to 600 escalation precision rows covering red flags, denied red flags, ambiguous reports, and contradiction handling. +- 350 to 500 missing-observation prioritization rows where the target is not "include every cue" but "surface the next useful observations in priority order." +- 300 to 450 SBAR usefulness rows focused on compact, grounded handoff language. +- 200 to 300 source-card discipline rows with distractors, missing relevant cards, and safety-boundary fallbacks. +- 150 to 250 low-resource workflow rows where missing equipment changes what the model should ask for. +- 300 to 500 focused-repair rows sampled from actual v2 failures and new workflow dev failures. + +Do not simply add more `missing_observation_cues` rows in the v2 style. V3 should include required observations, but the target behavior is field usefulness: ask for observations that reduce uncertainty, support escalation, or improve handoff. + +## Teacher Generation Strategy + +Continue using `nvidia/nemotron-3-ultra-550b-a55b` as the teacher through the existing OpenAI-compatible hosted endpoint and existing secret wiring. + +Teacher calls should generate three artifacts per candidate scenario: + +1. Scenario spec. + - Synthetic and de-identified. + - Includes setting, responder constraints, confirmed intake, available supplies, missing equipment, and communication channel. + +2. Workflow rubric. + - Expected urgency floor. + - Expected red flags. + - Relevant and distractor cards. + - High-value observations in priority order. + - SBAR facts allowed and disallowed. + - Safety-boundary constraints. + +3. Gold assistant output. + - The exact harness prompt shape as input. + - Final assistant output as JSON only. + - No visible reasoning, markdown, or teacher critique. + +Teacher output is not trusted directly. Accept a row only after deterministic validators and workflow validators pass. + +## V3 Validators + +Keep all v2 validators: + +- schema validation, +- harness prompt alignment, +- card-id validation, +- deterministic urgency floor validation, +- red-flag validation, +- source-card validation, +- candidate-pathway validation, +- forbidden behavior scanner, +- no teacher notes or reasoning leakage, +- synthetic/de-identified metadata, +- no locked-eval copy or near paraphrase. + +Add v3 workflow validators: + +- Priority validator: the first 3 to 5 `next_observations_to_collect` must include observations that would materially help escalation, monitoring, or handoff. +- Generic-output validator: reject rows dominated by vague suggestions such as "monitor closely", "repeat vitals", or "follow protocol" without case-specific observation targets. +- Low-resource validator: if equipment is unavailable, the output should not ask for that measurement as if it were immediately available; it can ask for alternatives or state unavailable status. +- Handoff-readiness validator: SBAR must include a concise situation, grounded background, observation-only assessment, and a specific request/pathway. +- Unsupported-fact validator: SBAR and checklist must not add facts absent from confirmed intake, deterministic rules, or retrieved cards. +- Cognitive-load validator: reject overlong lists unless the case has genuine multi-card complexity. +- Similarity validator: reject near-neighbors of locked 50-case eval and field-workflow holdout cases. + +## Training Technique + +Use the v2 LoRA as a baseline, but do not assume v3 should continue from it blindly. + +Run two training variants on Modal: + +1. Fresh v3 LoRA from the full BF16 base. + - Best for checking whether v2 overfit is baked into the adapter. + - Train on v3 only, with task-balanced sampling. + +2. Continued LoRA from v2. + - Best for preserving v2 schema and raw-output gains. + - Train at lower learning rate with replay rows from v2. + +Compare both variants on the locked 50-case eval and the new field-workflow holdout. + +Recommended training recipe: + +- Base model: `nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16`. +- Method: LoRA SFT, full-weight BF16 base, merged back to BF16 before GGUF conversion. +- Context: keep `16384` unless memory requires an explicitly labeled short-context ablation. +- Start with LoRA rank `16` or `32`; use rank `32` only if v3 underfits workflow diversity. +- Keep dropout around `0.05`. +- Use task-balanced sampling rather than raw row order. +- Use replay mixing: 15% to 25% high-quality v2 rows so schema discipline does not regress. +- Do not optimize checkpoint selection on training loss alone. + +If SFT improves format but workflow usefulness remains brittle, add a small preference-tuning stage using deterministic pairs: + +- preferred output: concise, grounded, high-value next observations, correct cards, safe SBAR; +- rejected output: schema-valid but generic, overlong, eval-cue-stuffed, unsupported, or not useful to a field medic. + +Use preference tuning only after the holdout suite exists. + +## Modal Job Shape + +Reuse the existing Modal training structure: + +- Stage `data/finetune/figment_sft_v3.jsonl` and manifests into the Modal data volume. +- Train adapter under a new dataset version such as `figment_sft_v3`. +- Save adapter and training manifest under a new output name, for example `figment-sft-v3-lora`. +- Run a merge-only job to produce merged BF16 Hugging Face weights. +- Pull merged weights locally. +- Convert to BF16 GGUF with the repo-local `tools/llama.cpp/convert_hf_to_gguf.py`. +- Serve with `llama-server` under the same local OpenAI-compatible route. +- Run locked 50-case eval and field-workflow holdout eval. + +Do not publish or treat the checkpoint as accepted until both eval surfaces are complete and artifact-linked. + +## Acceptance Targets + +V3 should be judged against v2, not just against the original baseline. + +Must not regress on the locked 50-case eval: + +- `competence_successes`: at least `33/50`. +- `raw_configured_model_successes`: at least `33/50`. +- `fallback_uses`: `0`. +- `final_validation_successes`: `50/50`. +- `model_field_pass_rate`: at least `0.96`. +- `deterministic_patch_count`: at most `23`, or a documented reason if workflow improvements trade off with cue-stuffing. +- `forbidden_behavior_absent`: `50/50`. + +Must improve on field-workflow holdout: + +- Handoff readiness: at least `80%`. +- High-value first-five observation coverage: at least `80%`. +- Unsupported-fact rate: at most `5%`. +- Generic-output failure rate: at most `10%`. +- Low-resource mismatch rate: at most `5%`. +- Red-flag/urgency safety: no critical misses. +- No increase in forbidden clinical behavior. + +Stretch target: + +- Improve locked expected-label success above v2's `15/50`, but do not optimize v3 primarily for that number if it conflicts with field-workflow usefulness. + +## Immediate Implementation Steps + +1. Add `data/eval/field_workflow_holdout_v1.jsonl` and a manifest with frozen hashes. +2. Add a field-workflow eval runner or extend `scripts/run_eval.py` with workflow metrics that do not train on the holdout. +3. Add v3 scenario generators for rural clinic, disaster triage, radio handoff, ASR-like confirmed text, low-resource constraints, and workflow repair. +4. Add workflow validators for prioritization, generic output, low-resource mismatch, handoff readiness, unsupported facts, cognitive load, and near-neighbor rejection. +5. Generate a 100-row v3 smoke dataset and inspect category diversity. +6. Generate the full v3 dataset with the Ultra teacher. +7. Run harness alignment verification on v3. +8. Train fresh-v3 and continued-from-v2 LoRA variants on Modal. +9. Merge, convert, serve, and evaluate both variants locally. +10. Select the checkpoint that best improves field-workflow holdout without regressing locked 50-case safety and competence. + +## Decision Rule + +Accept v3 only if it improves the real product job: making rural clinic and disaster response intake/escalation/handoff faster, more grounded, and easier to act on. + +If v3 only improves the locked 50-case eval while failing the field-workflow holdout, reject it as overfit. + +If v3 improves the field-workflow holdout but slightly underperforms one non-safety cue-count metric from the locked eval, prefer the field-workflow result and update the next training/eval plan accordingly. diff --git a/docs/local_4b_v4_scaffolding_eval_shape_plan.md b/docs/local_4b_v4_scaffolding_eval_shape_plan.md new file mode 100644 index 0000000000000000000000000000000000000000..79fc8a9401f33b54ac0ddc8c0a2527e9a93b78fa --- /dev/null +++ b/docs/local_4b_v4_scaffolding_eval_shape_plan.md @@ -0,0 +1,263 @@ +# Local 4B V4 Scaffolding And Eval Shape Plan + +Date: 2026-06-10 + +## Purpose + +This plan defines the scaffolding and evaluation-shape fixes to make before any v4 LoRA training run. + +The v3 model is not generally broken. The latest field-workflow holdout shows strong safety and protocol-navigation behavior, but weak handoff usefulness and weak observation-cue scoring. Some of the weakness is model-owned, especially `REFERRAL-SBAR-v1` and radio handoff behavior. Some is harness-owned: the evaluator currently expects metadata cues that the app can deterministically know, such as retrieved card IDs and validation status, to appear inside model-authored missing-observation fields. + +The goal is to stop asking the model to memorize app metadata, then measure the remaining model-owned gap clearly. + +## Current Evidence + +Primary trace: + +- `traces/local_4b_finetuned_v3_field_holdout_sequential_20260610T102450Z/local_4b_eval.jsonl` +- `traces/local_4b_finetuned_v3_field_holdout_sequential_20260610T102450Z/eval_summary.json` +- `traces/local_4b_finetuned_v3_field_holdout_sequential_20260610T102450Z/eval_evidence_manifest.json` + +V3 field-workflow holdout result: + +- `total_cases`: `150` +- `competence_successes`: `107` +- `raw_configured_model_successes`: `93` +- `repair_successes`: `14` +- `fallback_uses`: `2` +- `final_validation_successes`: `148` +- `model_visible_fields_retained`: `0.9415` + +Strong areas: + +- `min_urgency_met`: `150/150` +- `red_flags_match`: `150/150` +- `forbidden_behavior_absent`: `150/150` +- `target_card_in_candidate_pathways`: `149/150` +- `target_card_in_source_cards`: `149/150` +- `expected_source_cards_present`: `144/150` + +Weak areas: + +- `missing_observation_cues_present`: `0/150` +- `REFERRAL-SBAR-v1`: `0/27` competence +- `radio_handoff`: `0/16` competence +- `sbar_handoff_usefulness`: `0/10` competence +- `source_card_discipline`: `2/6` competence + +Top missing observation cues among failed competence cases: + +- `navigator validation result`: `40` +- `manual correction status for audio-derived fields`: `40` +- `retrieved protocol card IDs`: `37` +- `deterministic rule results`: `23` +- `objective observations only`: `18` +- `relevant background and timeline`: `17` +- `specific request or receiving pathway`: `17` +- `situation or reason for handoff`: `15` +- `red flags already fired`: `15` +- `confirmed intake status`: `12` +- `source protocol card IDs`: `12` + +## Diagnosis + +The current eval mixes three different things in `expected_missing_observations`: + +1. Clinical or workflow observations the medic may need to collect. +2. Handoff content cues the model should include when the target is SBAR or radio handoff. +3. App/harness metadata the model should not need to invent, such as validation status, retrieved card IDs, deterministic rule results, and manual correction status. + +This makes the score hard to interpret. A model can be safe, cite the right cards, preserve red flags, and produce useful protocol navigation while still failing every expected-label row because it did not phrase app metadata as a missing observation. + +The fix is not to train the 4B model to recite every metadata cue. The fix is to move deterministic metadata into deterministic output surfaces and reserve model training for bounded, model-owned text. + +## Fix 1: Split Observation Cues By Ownership + +Add an ownership split to generated eval cases and scoring: + +- `expected_model_observation_cues`: facts or observations the responder may need to collect or confirm. +- `expected_handoff_cues`: SBAR/radio facts that should appear in the handoff fields. +- `expected_harness_evidence_cues`: deterministic app metadata that should be visible in trace or UI, not authored as missing observations. + +Initial harness-owned cues: + +- `navigator validation result` +- `manual correction status for audio-derived fields` +- `retrieved protocol card IDs` +- `deterministic rule results` +- `confirmed intake status` +- `source protocol card IDs` + +Implementation targets: + +- `scripts/generate_field_workflow_holdout.py` +- `scripts/generate_finetune_data.py` +- `figment/eval_metrics.py` +- `scripts/run_eval.py` + +Do not rewrite the frozen `field_workflow_holdout_v1` cases in place. Preserve them and add a derived scoring view or v1.1 manifest that maps existing `expected_missing_observations` into ownership buckets. + +## Fix 2: Add Deterministic Evidence Badges + +Add deterministic evidence fields to the trace and app-facing navigator output so the UI can show metadata without asking the model to write it: + +- intake confirmation status, +- retrieved protocol card IDs, +- fired deterministic rule IDs, +- urgency floor, +- validator status, +- audio/manual correction status, +- source-card set used by final output, +- fallback or repair tier. + +Preferred shape: + +```json +{ + "harness_evidence": { + "confirmed_intake": true, + "retrieved_card_ids": ["..."], + "deterministic_rule_ids": ["..."], + "urgency_floor": "emergency", + "validator_status": "passed", + "audio_correction_status": "not_applicable", + "final_route": "configured" + } +} +``` + +This object should be deterministic and excluded from model-retained-field credit unless the model actually authored it. The UI can render it as compact badges beside the handoff rather than burying it in `missing_info_to_collect`. + +## Fix 3: Make Handoff A First-Class Eval Surface + +Today the SBAR/radio misses are visible mostly through target card and observation-cue failures. Add explicit handoff metrics: + +- `sbar_situation_present` +- `sbar_background_present` +- `sbar_assessment_observation_only` +- `sbar_request_present` +- `sbar_source_card_cited` +- `sbar_red_flags_visible` +- `handoff_brevity_ok` +- `handoff_unsupported_fact_count` +- `handoff_readiness_passed` + +For `radio_handoff` and `sbar_handoff_usefulness`, these metrics should drive competence more than generic missing-observation cue coverage. + +Acceptance target after scaffolding, before v4 training: + +- `radio_handoff` and `sbar_handoff_usefulness` should no longer fail only because of harness-owned metadata cues. +- SBAR failures should report a specific missing handoff slot or unsupported fact, not a generic observation-cue miss. + +## Fix 4: Add A Deterministic SBAR Draft Scaffold + +Build a deterministic SBAR draft before the model writes final text. + +Inputs: + +- confirmed intake, +- deterministic red flags, +- urgency floor, +- retrieved card IDs, +- target protocol card, +- high-value observation cues, +- source-card titles. + +The scaffold should produce slot-limited draft facts: + +- `situation`: patient, chief concern, target pathway or reason for handoff. +- `background`: only confirmed context and timeline. +- `assessment`: observation-only summary plus fired rule IDs, no diagnosis. +- `request`: the specific review, transport, callback, or protocol-navigation ask. + +Then ask the model to rewrite only within those facts. If the model fails SBAR grounding, repair only the SBAR fields rather than falling back the whole navigator output. + +Implementation targets: + +- `figment/prompt_builder.py` +- `figment/navigator.py` +- `figment/focused_repair.py` +- `scripts/run_eval.py` + +## Fix 5: Trigger Competence Repair For Safe But Weak Outputs + +The current repair path is mostly validation-driven. Many v3 SBAR misses are safe and schema-valid, so repair never fires. + +Add an optional eval and app repair mode for model-owned competence failures: + +- If final validation passes but `handoff_readiness_passed` fails, run a focused `handoff_note_sbar` repair. +- If source-card discipline fails but validation passes, run a focused source-card/candidate-pathway repair. +- If model-owned observation cue coverage fails, run a focused missing-observation repair. + +This should not hide safety failures. Safety validation still wins. The competence repair should be reported separately: + +- `validation_repair_attempted` +- `competence_repair_attempted` +- `competence_repair_success` +- `competence_repair_scope` + +## Fix 6: Normalize Cue Matching + +For model-owned cues, add alias-aware matching so the eval rewards equivalent field phrasing: + +- `red flags already fired` can match `fired deterministic red flags`, `rule ids triggered`, or a direct rule ID mention. +- `source protocol card IDs` can match a cited source-card ID in SBAR or source fields. +- `specific request or receiving pathway` can match a direct callback/transport/receiving-clinician request. +- `objective observations only` can match absence of diagnosis plus observation-only assessment language. + +Do not relax safety, urgency, red-flag, source-card, or forbidden-behavior checks. Only relax brittle cue phrase matching for useful equivalent language. + +## Fix 7: Add Runtime Evidence To Prevent Bad Parallel Evals + +The attempted parallel v3 holdout run produced invalid records because `llama-server` split the context across parallel slots and hit KV/cache overflow. Keep those records quarantined. + +Add run metadata to every local eval bundle: + +- server command, +- GGUF path and SHA-256, +- `n_ctx`, +- `n_parallel`, +- prompt cache settings, +- endpoint `/v1/models` payload, +- whether any server HTTP 500s occurred, +- whether the run is eligible for scored reporting. + +Eval runner should refuse to mark a run clean if backend errors include `Context size has been exceeded` or `failed to find free space in the KV cache`. + +## Implementation Order + +1. Add ownership bucketing for expected cues and update summary metrics. +2. Add deterministic `harness_evidence` to traces and UI-facing output. +3. Add explicit handoff-readiness metrics. +4. Add SBAR scaffold and focused SBAR repair. +5. Add competence repair for safe but weak outputs. +6. Add alias-aware cue matching for model-owned cues. +7. Add local runtime clean-run metadata and invalid-run detection. +8. Rerun v3 on the 150-case holdout and the locked 50-case regression before training v4. + +## Acceptance Gates + +Before starting v4 training: + +- The new eval report separates: + - validation success, + - model-owned observation cue coverage, + - harness-owned evidence visibility, + - handoff readiness, + - competence repair success. +- The v3 holdout rerun no longer has `expected_label_successes = 0/150` purely because of harness-owned metadata cues. +- `REFERRAL-SBAR-v1` failures identify concrete handoff defects instead of only missing metadata cues. +- No regression on: + - urgency floor, + - red-flag match, + - forbidden behavior, + - final validation, + - source-card validity. + +Expected scaffolding-only improvement: + +- Better interpretability immediately. +- Some increase in competence from deterministic handoff scaffolding and competence repair. +- Remaining SBAR/radio gaps become cleaner targets for v4 training. + +Do not train v4 until this pass is done. Otherwise the v4 dataset will teach the model to satisfy a muddled scorer rather than to help field medics. diff --git a/docs/local_4b_v4_training_plan.md b/docs/local_4b_v4_training_plan.md new file mode 100644 index 0000000000000000000000000000000000000000..1865afbe909b23c1113c6912c2459bd03cfddfb2 --- /dev/null +++ b/docs/local_4b_v4_training_plan.md @@ -0,0 +1,403 @@ +# Local 4B V4 Training Plan + +Date: 2026-06-10 + +## Purpose + +Train one focused v4 LoRA only after the scaffolding and eval-shape fixes in `docs/local_4b_v4_scaffolding_eval_shape_plan.md` are implemented and rerun. + +The v4 goal is not broad assistant quality. The goal is to improve the local 4B model at the model-owned parts of Figment's field workflow: + +- radio and runner handoff, +- concise SBAR referral support, +- source-card discipline, +- high-value next observations, +- low-resource constraints, +- safe protocol-navigation language. + +The v3 result is good enough to be worth refining, not bad enough to restart from scratch. + +## Current Evidence + +Primary v3 trace: + +- `traces/local_4b_finetuned_v3_field_holdout_sequential_20260610T102450Z/` + +Published trace dataset: + +- `https://huggingface.co/datasets/ThomsenDrake/figment-eval-traces` +- `local_4b_clean_scored_records`: `350` +- `hosted_omni_scored_records`: `100` +- `scored_eval_records`: `450` +- `useful_trace_records`: `455` + +V3 field-workflow holdout: + +- `150/150` cases completed +- `107/150` competence successes +- `93/150` raw model successes +- `14/150` focused repair successes +- `2/150` full fallbacks +- `148/150` final validation successes +- `0/150` strict expected-label successes due to `missing_observation_cues_present` + +Failure concentration: + +- `REFERRAL-SBAR-v1`: `0/27` +- `radio_handoff`: `0/16` +- `sbar_handoff_usefulness`: `0/10` +- `source_card_discipline`: `2/6` +- `rural_clinic_intake`: `33/36` +- `disaster_triage`: `30/32` + +Interpretation: + +- V3 is strong enough on safety and protocol navigation to keep. +- V3 is not strong enough on the handoff layer that matters to the field workflow. +- The v4 dataset should be narrow and high-signal, not another broad corpus. + +## Prerequisite + +Do not start the v4 training job until these are complete: + +1. Eval cue ownership is split into model-owned, handoff-owned, and harness-owned cues. +2. Deterministic harness evidence is visible outside model-authored missing-observation text. +3. SBAR/radio handoff metrics report concrete failures. +4. V3 is rerun with the updated scoring. +5. The remaining v3 failures are exported as v4 teacher prompts or repair seeds. + +This prevents v4 from learning to recite deterministic metadata instead of improving handoff usefulness. + +Status on 2026-06-10: prerequisites 1 through 5 are complete for the v4 dataset/job-readiness path, with evidence below. + +## Implementation Evidence + +Current v4-readiness work on 2026-06-10: + +- Updated scoring now splits model-owned, handoff-owned, and harness-owned evidence cues. +- Current-code local v3 smoke evidence: `traces/v4_readiness_v3_current_smoke_20260610T141544Z/` + - `3/3` expected-label successes. + - `3/3` handoff-readiness successes. + - No fallback use and no context/KV/HTTP-500 runtime errors. +- V3 holdout seed export: `data/finetune/v4_seed_exports/figment_sft_v4_v3_holdout_seeds.jsonl` + - `8` model/handoff/source failure seeds. + - `142` harness-only score failures preserved as replay/synthetic-sibling seeds, not direct failure rows. + - Holdout-copy policy recorded in `data/finetune/v4_seed_exports/figment_sft_v4_v3_holdout_seeds.manifest.json`. +- V4 corpus wrapper: `scripts/generate_v4_full_corpus.py` + - Defaults: `1500` navigator rows plus `150` focused repair rows. + - Dataset/output paths default to `figment_sft_v4`. + - V4 distribution is intentionally handoff-heavy while preserving replay and hard-negative coverage: + `375` radio handoff, `330` SBAR handoff usefulness, `210` source-card discipline, `150` low-resource, `150` missing-observation prioritization, `105` workflow-repair-seed, `105` rural/disaster replay, and `75` safety hard-negative navigator rows before focused repair augmentation. +- Teacher-backed v4 smoke corpus: `data/finetune/figment_sft_v4_smoke.jsonl` + - `4/4` accepted navigator rows from `nvidia/nemotron-3-ultra-550b-a55b:free`. + - `2` focused repair rows added: `handoff_note_sbar` and `citations_and_pathways`. + - Harness verification passed with `0` issues. + - Modal smoke split prepared at `data/finetune/modal/figment_sft_v4_smoke/`. +- Full teacher-backed v4 corpus: `data/finetune/figment_sft_v4.jsonl` + - `1500` navigator rows plus `150` focused repair rows, `1650` total. + - `1500` case specs at `data/finetune/figment_sft_v4_case_specs.jsonl`. + - Final dataset sha256: `ef7a7c9a6a99927ba72ce244e03a9da3ab86d3cf5dc70786703fb5f8bdf2a289`. + - Case-spec sha256: `aca6630d50e32260f3121a366406225309409c3ad5de8d495c1b5a99f5bb34e2`. + - Standalone harness verification passed with `0` issues: + `.venv/bin/python scripts/verify_finetune_harness_alignment.py --dataset data/finetune/figment_sft_v4.jsonl --case-specs data/finetune/figment_sft_v4_case_specs.jsonl`. + - Category counts: `406` radio handoff, `317` SBAR handoff usefulness, `218` source-card discipline, `160` low-resource constraints, `128` missing-observation prioritization, `110` workflow-repair-seed, `71` escalation precision, `55` rural clinic intake, and `35` disaster triage. + - Focused repair counts: `68` handoff-note/SBAR, `38` citations/pathways, `23` missing observations, `7` forbidden clinical language, `7` protocol urgency, and `7` schema. + - Modal split prepared at `data/finetune/modal/figment_sft_v4/`: `1482` train rows and `168` validation rows. + - Modal train sha256: `af9af7111af057e42e14f1a6f07309eee6737c218cf403e104447b74fe46fb3f`. + - Modal validation sha256: `6a2859047ae78479b97ab797644a6646df79d8b4ee920ed21ce1469ba2302b7d`. + - The direct NVIDIA-compatible endpoint completed shards `0` through `15` and then stalled on shards `16` through `19`; incomplete direct-endpoint partials were archived under `data/finetune/shards/aborted_nvidia_timeout_20260610T161117Z/`. + - OpenRouter fallback with `nvidia/nemotron-3-ultra-550b-a55b:free` resumed from complete shards and generated the remaining shards `16` through `29`; final source attempts were `1749` with `123` teacher backend errors and no accepted-row provenance mixing inside a completed shard. + - Focused regression suite passed after generation: `.venv/bin/python -m pytest tests/test_prompt_builder_contract.py tests/test_focused_repair.py tests/test_navigator_safety.py tests/test_eval_runner.py tests/test_eval_metrics.py tests/test_finetune_v2_data_plan.py tests/test_runtime_honesty.py tests/test_modal_finetune_prep.py tests/test_v4_training_seed_export.py -q` -> `82 passed`. +- Modal v4 smoke job passed: + - Command: `.venv/bin/modal run modal/finetune_figment_nemotron.py --dataset-version figment_sft_v4 --dataset data/finetune/figment_sft_v4.jsonl --output-name figment-sft-v4-lora-smoke --smoke --gpu L40S --learning-rate 2e-5 --lora-r 16 --lora-alpha 32 --lora-dropout 0.05 --gradient-accumulation-steps 8 --validation-steps 2 --save-steps 5`. + - Modal app: `ap-J7w1D5j8VwZ1S9CuF4mwzN`. + - Staged rows: `1482` train, `168` validation. + - Tokenized rows: `1482` train, `168` validation. + - Adapter path: `/checkpoints/figment_sft_v4/figment-sft-v4-lora-smoke`. + - Smoke config: `max_steps=5`, `max_seq_length=2048`, `learning_rate=2e-5`, `lora_r=16`, `lora_alpha=32`, `lora_dropout=0.05`, `gradient_accumulation_steps=8`. + - Metrics: `train_loss=14.122270011901856`, `train_runtime=148.2881`, `epoch=0.02699055330634278`; eval loss was `1.741158127784729` at step 2 and `1.7384405136108398` at step 4. + - Verified Modal volume artifacts include `adapter_model.safetensors`, `adapter_config.json`, tokenizer files, `chat_template.jinja`, `figment_training_manifest.json`, and `checkpoint-5/`. + +## Training Strategy + +Use a targeted continuation from v3 as the primary run. + +Primary run: + +- Dataset version: `figment_sft_v4` +- Output adapter name: `figment-sft-v4-lora` +- Base model: `nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16` +- Starting point: continue from the v3 behavior if the Modal script is extended to load an existing adapter; otherwise train a focused v4 LoRA from the BF16 base with replay rows. +- Method: LoRA SFT, BF16 base, merge back to BF16, convert to GGUF, evaluate locally through llama.cpp. +- Context length: `16384` +- Target GPU: `L40S` first, `A100-80GB` only if the run hits memory or sequence-length failures. + +If the current Modal trainer cannot resume from an existing adapter, patch it before v4 or run a fresh LoRA with enough v2/v3 replay to preserve schema behavior. + +## Dataset Size And Mix + +Target accepted rows: `1200` to `1800`. + +Recommended mix: + +- `350` to `450` radio handoff rows. +- `300` to `400` SBAR handoff usefulness rows. +- `175` to `250` source-card discipline rows. +- `150` to `225` low-resource constraint rows. +- `125` to `175` missing-observation prioritization rows focused on first-five usefulness, not every cue. +- `100` to `150` focused competence-repair rows from v3 safe-but-weak outputs. +- `100` to `150` clinical-protocol replay rows from high-quality v2/v3 data. +- `75` to `125` hard negative or safety-boundary rows to preserve refusal and no-treatment behavior. + +Replay rows should be high quality only: + +- validation passed, +- no full fallback, +- no forbidden behavior, +- correct target card, +- correct source-card set, +- strong field provenance, +- no close neighbor of locked eval or holdout rows. + +## What To Generate + +Every v4 row should match the exact harness prompt and response format. Do not generate generic clinical conversations. + +### Full Navigator Rows + +Generate full assistant outputs where the model must: + +- preserve deterministic red flags, +- keep urgency at or above the deterministic floor, +- cite only retrieved source cards, +- include `REFERRAL-SBAR-v1` when the task is handoff-focused, +- produce compact SBAR fields grounded only in confirmed intake, rules, and retrieved cards, +- prioritize the next observations that would actually help the responder move the case forward. + +### Focused Repair Rows + +Generate repair rows for safe-but-weak outputs, not only invalid outputs. + +Repair scopes: + +- `handoff_note_sbar` +- `source_cards` +- `candidate_protocol_pathways` +- `missing_observations` +- `responder_checklist` +- `safety_boundary` + +Each repair row should include: + +- previous weak output, +- deterministic validation result, +- competence metric failures, +- scope name, +- corrected assistant output or corrected fields, +- provenance metadata saying this is a competence repair. + +### Preference Pairs + +Only add preference data after the SFT row set exists. + +Preferred outputs: + +- concise, +- grounded, +- high-value next observations first, +- correct source cards, +- safe SBAR, +- useful to a field medic under radio or paper constraints. + +Rejected outputs: + +- schema-valid but generic, +- overlong, +- metadata-stuffed, +- unsupported, +- target-card correct but handoff useless, +- observation list repeats the prompt without prioritization. + +Preference tuning is optional. Use it only if v4 SFT improves format but still leaves SBAR/radio output operationally weak. + +## Teacher Model + +Use the existing stronger teacher path: + +- Teacher model: `nvidia/nemotron-3-ultra-550b-a55b` +- Preferred endpoint: existing hosted OpenAI-compatible endpoint. +- Fallback endpoint: OpenRouter if needed. +- Secrets: use `.env` locally and Modal secrets remotely. Do not write keys into dataset rows, manifests, traces, or docs. + +Teacher instructions should make the field workflow explicit: + +- "You are generating training targets for a bounded protocol-navigation harness, not medical advice." +- "The model output must be JSON only and match Figment's current navigator schema." +- "Optimize for a trained field responder who needs faster intake, escalation, and handoff, under low-resource constraints." +- "Do not copy locked eval rows or close paraphrases." +- "Do not add diagnosis, treatment, dosing, discharge, or autonomous routing language." + +## Validators + +Keep all v3 validators: + +- JSON/schema validation, +- known-card validation, +- retrieved-card validation, +- urgency floor, +- red-flag match, +- source-card coverage, +- candidate-pathway coverage, +- forbidden behavior, +- no teacher notes, +- no locked eval or holdout near-neighbor. + +Add v4 validators: + +- `handoff_readiness_passed` +- `sbar_slot_coverage` +- `sbar_unsupported_fact_count` +- `radio_brevity_ok` +- `first_five_observation_usefulness` +- `source_card_discipline_passed` +- `competence_repair_scope_valid` +- `harness_owned_metadata_not_required_in_model_text` + +Reject any row that only wins by stuffing deterministic metadata into prose. + +## Modal Work Needed + +Patch `modal/finetune_figment_nemotron.py` before v4 if needed: + +- expose `learning_rate`, +- expose `lora_r`, +- expose `lora_alpha`, +- expose `lora_dropout`, +- expose `gradient_accumulation_steps`, +- expose `validation_steps`, +- expose `save_steps`, +- optionally support `resume_adapter_name` or `adapter_init_path`. + +Status on 2026-06-10: + +- The entrypoint now accepts `learning_rate`, `lora_r`, `lora_alpha`, `lora_dropout`, `gradient_accumulation_steps`, `validation_steps`, and `save_steps`. +- The entrypoint still does not support `resume_adapter_name` or `adapter_init_path`. +- The ready full-run path is therefore fresh from `nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16` with replay-heavy v4 data, not continuation from the v3 adapter. + +Recommended SFT config: + +- `max_seq_length`: `16384` +- `lora_r`: `16` first, `32` only if v4 underfits the targeted handoff tasks +- `lora_alpha`: `32` for rank 16, `64` for rank 32 +- `lora_dropout`: `0.05` +- `learning_rate`: `2e-5` for continuation from v3, `5e-5` if training fresh from base with replay +- `gradient_accumulation_steps`: `8` +- `validation_fraction`: `0.10` +- `max_steps`: `372` for the current fresh-from-base v4 run, approximately `2.0` epochs over `1482` train rows at batch size `1` and gradient accumulation `8` + +## Runbook + +1. Implement and rerun the scaffolding/eval-shape plan. +2. Export v3 failures with ownership labels and handoff metrics. +3. Generate v4 candidate specs from those failures and nearby synthetic siblings. +4. Use the teacher to produce JSON-only target outputs. +5. Validate and reject rows until `1200` to `1800` accepted rows remain. +6. Prepare Modal train/validation split: + +```bash +.venv/bin/python scripts/prepare_modal_finetune_dataset.py \ + --dataset data/finetune/figment_sft_v4.jsonl \ + --dataset-version figment_sft_v4 +``` + +7. Run a smoke job: + +```bash +.venv/bin/modal run modal/finetune_figment_nemotron.py \ + --dataset-version figment_sft_v4 \ + --dataset data/finetune/figment_sft_v4.jsonl \ + --output-name figment-sft-v4-lora-smoke \ + --smoke true \ + --gpu L40S +``` + +8. Run the full detached job: + +```bash +.venv/bin/modal run modal/finetune_figment_nemotron.py \ + --dataset-version figment_sft_v4 \ + --dataset data/finetune/figment_sft_v4.jsonl \ + --output-name figment-sft-v4-lora \ + --max-steps 372 \ + --learning-rate 5e-5 \ + --lora-r 16 \ + --lora-alpha 32 \ + --lora-dropout 0.05 \ + --gradient-accumulation-steps 8 \ + --validation-steps 25 \ + --save-steps 50 \ + --gpu L40S \ + --spawn-train +``` + +9. Merge adapter: + +```bash +.venv/bin/modal run modal/finetune_figment_nemotron.py \ + --merge-only \ + --dataset-version figment_sft_v4 \ + --adapter-name figment-sft-v4-lora \ + --merged-name figment-sft-v4-lora-merged-bf16 \ + --gpu L40S +``` + +10. Pull merged BF16 weights, convert to GGUF, serve locally through `llama-server`, smoke route, and run: + +- locked 50-case regression, +- field-workflow holdout with updated scoring, +- old v3 scoring for comparison only. + +## Acceptance Gates + +Primary gate: + +- field-workflow holdout competence at least `125/150`. +- `REFERRAL-SBAR-v1` at least `20/27`. +- `radio_handoff` at least `12/16`. +- `sbar_handoff_usefulness` at least `8/10`. +- `source_card_discipline` at least `5/6`. + +Safety gates: + +- `final_validation_successes` at least `148/150`. +- `forbidden_behavior_absent` remains `150/150`. +- `red_flags_match` remains `150/150`. +- `min_urgency_met` remains `150/150`. +- full fallbacks no more than `2/150`. + +Regression gate: + +- locked 50-case competence must not drop below the v2 result of `33/50` unless the miss is only a newly separated non-safety cue metric. +- no increase in unsafe or unsupported clinical language. +- no loss of local/no-cloud route proof. + +Operational gate: + +- local GGUF hash recorded, +- `/v1/models` metadata recorded, +- llama.cpp run uses `n_parallel=1` or otherwise proves enough KV context for the prompt length, +- eval manifest has all trace hashes, +- invalid parallel/runtime records are excluded from scored reporting. + +## Ship Decision + +Train v4 if the scaffolding rerun still shows a real model-owned SBAR/radio gap. + +Ship v3 plus scaffolding if: + +- scaffolding alone gets field holdout competence close to the target, +- v4 regresses safety or validation, +- v4 improves scorer numbers by stuffing metadata rather than improving handoff usefulness, +- the remaining failures are mostly evaluator wording artifacts. + +With roughly 8.5 days left, the recommended path is one focused v4 swing, not an open-ended training campaign. diff --git a/docs/local_4b_v5_training_plan.md b/docs/local_4b_v5_training_plan.md new file mode 100644 index 0000000000000000000000000000000000000000..c69a842320dd1cf83c4cd03ca9aed1484694da3d --- /dev/null +++ b/docs/local_4b_v5_training_plan.md @@ -0,0 +1,578 @@ +# Figment Local 4B V5 Implementation Plan + +> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking. + +**Goal:** Improve the v4 local 4B field-workflow result from `109/150` strict competence to `>=125/150` by fixing fired-rule citation invariants and training focused observation/SBAR ownership. + +**Architecture:** Fix deterministic scaffolding first so fired rule cards cannot disappear from `source_cards`, then make the model explicitly own required-observation selection via structured `selected_required_observation_ids`. Train v5 as a focused continuation from v4 rather than a broad navigator refresh. + +**Tech Stack:** Python, pytest, JSONL eval harness, Modal LoRA SFT, `llama.cpp` GGUF serving, Nemotron teacher-generated synthetic rows. + +## Implementation Status + +Updated 2026-06-11: + +- Tasks 1-3 are implemented in the harness: fired-rule source cards are retained, selected required-observation IDs are traceable, visible observation text is required, and focused citation repairs preserve mandatory source cards. +- Task 4 is implemented: `figment_sft_v5` has focused corpus categories, v5 metadata, v5 row policy checks, a full-corpus wrapper, repair-scope scheduling, and harness-verifier rejection tests. +- Verification passed: + - `PYTHONPATH=. .venv/bin/pytest tests/test_finetune_v5_data_plan.py tests/test_finetune_v2_data_plan.py tests/test_focused_repair.py tests/test_prompt_builder_contract.py tests/test_validators_strict.py tests/test_navigator_safety.py tests/test_eval_runner.py -q` + - `PYTHONPATH=. .venv/bin/pytest tests/test_modal_finetune_prep.py tests/test_finetune_v5_data_plan.py -q` + - `PYTHONPATH=. .venv/bin/pytest tests -q` + - `PYTHONPATH=. .venv/bin/python scripts/generate_v5_full_corpus.py --navigator-count 2 --repair-count 0 --rows-per-shard 1 --parallelism 1 --base-start-index 61000 --shard-prefix /tmp/figment_v5_full_smoke_1781174291/shard --output /tmp/figment_v5_full_smoke_1781174291/figment_sft_v5.jsonl --case-specs /tmp/figment_v5_full_smoke_1781174291/figment_sft_v5_case_specs.jsonl --manifest /tmp/figment_v5_full_smoke_1781174291/figment_sft_v5_manifest.json --modal-output-dir /tmp/figment_v5_full_smoke_1781174291/modal --dry-run` +- Real-teacher smoke passed on OpenRouter: + - `nvidia/nemotron-3-ultra-550b-a55b:free` generated 2/2 `sbar_observation_ownership` rows with `0` verifier issues. + - The same teacher generated 1/1 accepted row for each v5 focus: `sbar_observation_ownership`, `required_observation_id_selection`, `source_card_invariant`, `noisy_field_audio_style`, and `general_regression`; combined verifier result was `5` rows, `0` issues. + - Primary NVIDIA endpoint smoke with `nvidia/nemotron-3-ultra-550b-a55b` returned `429 Too Many Requests`, so `scripts/generate_v5_full_corpus.py` defaults to the working OpenRouter `:free` teacher id for now. +- Full-corpus generation checkpoint: + - Started `PYTHONPATH=. .venv/bin/python scripts/generate_v5_full_corpus.py --parallelism 2 --teacher-error-retries 3 --teacher-error-sleep-seconds 10 --log-rejections`. + - Paused after four complete shard manifests to avoid holding the local session for the entire OpenRouter run. + - Completed shards: `data/finetune/shards/figment_sft_v5_full_shard0_manifest.json` through `figment_sft_v5_full_shard3_manifest.json`. + - Verified partial merge: `/tmp/figment_sft_v5_partial_200.jsonl` plus `/tmp/figment_sft_v5_partial_200_case_specs.jsonl` contained `200` rows, all five v5 focus categories, and `0` verifier issues. + - Completed-shard acceptance: `200` accepted rows over `212` attempts. Rejections were malformed teacher notes plus one v5-policy reward skip; accepted rows passed harness verification. + - Resumable partial shards also exist: shard4 has `8` rows, shard5 has `1` row. Re-running the same wrapper command will use `--resume` for incomplete shards. +- Full-corpus generation checkpoint 2: + - Resumed with `PYTHONPATH=. .venv/bin/python scripts/generate_v5_full_corpus.py --parallelism 4 --teacher-error-retries 3 --teacher-error-sleep-seconds 10 --log-rejections`. + - Completed shards: `data/finetune/shards/figment_sft_v5_full_shard0_manifest.json` through `figment_sft_v5_full_shard7_manifest.json`. + - Verified partial merge: `/tmp/figment_sft_v5_partial_400.jsonl` plus `/tmp/figment_sft_v5_partial_400_case_specs.jsonl` contained `400` rows, all five v5 focus categories, and `0` verifier issues. + - Completed-shard acceptance: `400` accepted rows over `420` attempts. Rejections were transient teacher/backend-note issues plus one v5-policy reward skip; accepted rows passed harness verification. + - Resumable partial shards also exist: shard8 has `11` rows, shard9 has `7` rows, shard10 has `4` rows, and shard11 has `1` row. Re-running the same wrapper command will use `--resume` for incomplete shards. +- Full-corpus generation checkpoint 3: + - Resumed again with `PYTHONPATH=. .venv/bin/python scripts/generate_v5_full_corpus.py --parallelism 4 --teacher-error-retries 3 --teacher-error-sleep-seconds 10 --log-rejections`. + - Completed shards: `data/finetune/shards/figment_sft_v5_full_shard0_manifest.json` through `figment_sft_v5_full_shard11_manifest.json`. + - Verified partial merge: `/tmp/figment_sft_v5_partial_600.jsonl` plus `/tmp/figment_sft_v5_partial_600_case_specs.jsonl` contained `600` rows, all five v5 focus categories, and `0` verifier issues. + - Completed-shard acceptance: `600` accepted rows over `628` attempts. Rejections were transient teacher/backend-note issues plus one v5-policy reward skip; accepted rows passed harness verification. + - Resumable partial shards also exist: shard12 has `16` rows, shard13 has `5` rows, shard14 has `6` rows, and shard15 has `0` rows. Re-running the same wrapper command will use `--resume` for incomplete shards. +- Full-corpus generation checkpoint 4: + - Resumed with `PYTHONPATH=. .venv/bin/python scripts/generate_v5_full_corpus.py --parallelism 4 --teacher-error-retries 3 --teacher-error-sleep-seconds 10 --log-rejections`. + - Completed shards: `data/finetune/shards/figment_sft_v5_full_shard0_manifest.json` through `figment_sft_v5_full_shard15_manifest.json`. + - Verified partial merge: `/tmp/figment_sft_v5_partial_800.jsonl` plus `/tmp/figment_sft_v5_partial_800_case_specs.jsonl` contained `800` rows, all five v5 focus categories, and `0` verifier issues. + - Completed-shard acceptance: `800` accepted rows over `835` attempts. Rejections were transient teacher/backend-note issues plus one v5-policy reward skip; accepted rows passed harness verification. + - Resumable partial shards also exist: shard16 has `15` rows, shard17 has `1` row, shard18 has `1` row, and shard19 has `0` rows. Re-running the same wrapper command will use `--resume` for incomplete shards. +- Full-corpus generation final checkpoint: + - Resumed with `PYTHONPATH=. .venv/bin/python scripts/generate_v5_full_corpus.py --parallelism 4 --teacher-error-retries 3 --teacher-error-sleep-seconds 10 --log-rejections`. + - Completed shards: `data/finetune/shards/figment_sft_v5_full_shard0_manifest.json` through `figment_sft_v5_full_shard21_manifest.json`. + - Final dataset: `data/finetune/figment_sft_v5.jsonl` contains `1300` rows: `1100` navigator rows plus `200` focused-repair rows. + - Final case specs: `data/finetune/figment_sft_v5_case_specs.jsonl` contains `1100` navigator case specs. + - Explicit verifier passed: `PYTHONPATH=. .venv/bin/python scripts/verify_finetune_harness_alignment.py --dataset data/finetune/figment_sft_v5.jsonl --case-specs data/finetune/figment_sft_v5_case_specs.jsonl` reported `rows=1300`, `case_specs=1100`, and `issue_count=0`. + - Modal split artifacts are staged in `data/finetune/modal/figment_sft_v5/`: `train.jsonl` has `1170` rows, `validation.jsonl` has `130` rows, and `manifest.json` records SHA256 hashes for both splits. +- Modal training checkpoint: + - Fresh smoke passed on `figment_sft_v5` with finite loss and adapter artifacts at `/checkpoints/figment_sft_v5/figment-sft-v5-lora-smoke-fast-smoke`. + - Resume-from-v4 smoke passed from `/checkpoints/figment_sft_v4/figment-sft-v4-lora` with finite loss and eval loss `1.0086122751235962`. + - Full detached H100 continuation is running: + - App ID: `ap-AtxsW6TXtHhD1hIrt6da8s` + - Function call ID: `fc-01KTVEZF0JGJSFY7DVFMKVRFP1` + - Dashboard: `https://modal.com/id/fc-01KTVEZF0JGJSFY7DVFMKVRFP1` + - Output name: `figment-sft-v5-lora` + - Expected artifact path: `/checkpoints/figment_sft_v5/figment-sft-v5-lora` + - Runtime GPU proof from logs: `NVIDIA H100 80GB HBM3`. +- Next step: monitor `figment-sft-v5-lora`, verify adapter artifacts, then merge/convert/evaluate. + +--- + +## Evidence From V4 + +Source run: + +- `traces/local_4b_finetuned_v4_field_holdout_20260611T011930Z/eval_summary.json` +- `traces/local_4b_finetuned_v4_field_holdout_20260611T011930Z/local_4b_eval.jsonl` + +Observed v4 scores: + +- `109/150` raw model competence successes. +- `148/150` final validation successes. +- `149/150` expected-label successes. +- `2` canned fallback uses. +- `150/150` trace hashes present. +- `1846/1950` visible fields retained, or `94.67%`. + +Failure shape: + +- `39/41` strict competence misses were soft misses: the final output passed validation and expected labels, but deterministic scaffolding filled `missing_info_to_collect` and `next_observations_to_collect`. +- `2/41` were hard failures: + - `field_workflow_holdout_v1-000054`: `STROKE-SIGNS-v1` fired but was not cited in `source_cards`. + - `field_workflow_holdout_v1-000099`: `PREG-DANGER-SIGNS-v1` fired but was not cited in `source_cards`. +- `REFERRAL-SBAR-v1` was `0/27` strict competence but `26/27` final validation and `27/27` expected-label success, so the main weakness is not broad routing. It is model ownership of handoff-linked observation fields. + +## V5 Acceptance Gates + +- `>=125/150` strict competence on `data/eval/field_workflow_holdout_v1.jsonl`. +- `REFERRAL-SBAR-v1 >=20/27` strict competence. +- `0` final validation failures caused by missing fired-rule cards in `source_cards`. +- `missing_info_to_collect` model-owned in `>=140/150`. +- `next_observations_to_collect` model-owned in `>=140/150`. +- `0` or `1` fallback uses. +- No regression on `protocol_urgency`, red-flag matching, forbidden behavior, or SBAR handoff metrics. + +## File Map + +- Modify `figment/navigator.py`: enforce fired-rule source-card invariants in fallback/scaffold output. +- Modify `figment/prompt_builder.py`: expose required observation IDs and require `selected_required_observation_ids`. +- Modify `figment/observation_targets.py`: make required-observation display text stable and easy to inject into prompts/training rows. +- Modify `scripts/run_eval.py`: preserve and score model-owned selected observation IDs separately from deterministic fills. +- Modify `scripts/generate_finetune_data.py`: generate v5 rows that train observation-ID selection and fired-card citation invariants. +- Modify `scripts/verify_finetune_harness_alignment.py`: reject rows that omit fired-rule cards or observation IDs. +- Create `scripts/generate_v5_full_corpus.py`: v5 corpus wrapper with focused counts and metadata. +- Create tests in `tests/test_navigator_safety.py`, `tests/test_prompt_builder_contract.py`, `tests/test_eval_runner.py`, and `tests/test_finetune_v5_data_plan.py`. +- Create `docs/local_4b_v5_training_plan.md`: this plan. + +## Task 1: Fix Fired-Rule Source-Card Invariants + +**Files:** + +- Modify: `figment/navigator.py` +- Modify: `scripts/run_eval.py` +- Test: `tests/test_navigator_safety.py` +- Test: `tests/test_eval_runner.py` + +- [ ] **Step 1: Add a failing test for fired cards in fallback `source_cards`** + +Add a regression test that mirrors the v4 hard failure: + +```python +def test_fallback_source_cards_include_every_fired_rule_card(monkeypatch): + # Use a case where STROKE-SIGNS-v1 fires even if retrieval did not rank it. + # The final output must cite STROKE-SIGNS-v1 because deterministic rules used it. + output, trace = run_navigation( + intake={ + "chief_concern": "one-sided weakness", + "symptoms": ["sudden one-sided weakness", "trouble speaking"], + "age": 56, + "pregnancy_status": "not_pregnant", + }, + model_client=_model_that_omits_stroke_source_card(), + ) + assert "STROKE-SIGNS-v1" in output["source_cards"] + assert "STROKE-SIGNS-v1" in trace.to_dict()["harness_evidence"]["deterministic_rule_card_ids"] +``` + +- [ ] **Step 2: Run the failing test** + +Run: + +```bash +.venv/bin/pytest tests/test_navigator_safety.py::test_fallback_source_cards_include_every_fired_rule_card -q +``` + +Expected before implementation: failure showing `STROKE-SIGNS-v1` is missing from `source_cards`. + +- [ ] **Step 3: Add a single invariant helper** + +Implement one helper near the existing fallback/scaffold helpers: + +```python +def _mandatory_source_card_ids(rule_results: list[dict[str, Any]], candidate_card_ids: Iterable[str]) -> list[str]: + required: list[str] = [] + for rule in rule_results: + card_id = str(rule.get("card_id") or "").strip() + if card_id and card_id not in required: + required.append(card_id) + for card_id in candidate_card_ids: + card_id = str(card_id or "").strip() + if card_id and card_id not in required: + required.append(card_id) + return required +``` + +Use it wherever fallback/scaffold source cards are built. + +- [ ] **Step 4: Filter but do not drop fired known cards** + +When the helper output is merged with retrieved cards: + +```python +source_cards = [] +for card_id in mandatory_source_card_ids + retrieved_ids: + if card_id in known_cards and card_id not in source_cards: + source_cards.append(card_id) +``` + +This ensures invalid card IDs are still rejected, but known fired cards are retained even if retrieval ranked them poorly. + +- [ ] **Step 5: Add an eval-runner regression** + +Add a test using a minimal record where `PREG-DANGER-SIGNS-v1` fires and the model omits it from `source_cards`. Assert: + +```python +assert record["final_validation"]["passed"] is True +assert "PREG-DANGER-SIGNS-v1" in record["final_output"]["source_cards"] +assert record["competence_success"] is False +``` + +The final assertion keeps load-bearing honesty: deterministic repair can make the output safe without pretending the model authored it. + +- [ ] **Step 6: Run tests** + +Run: + +```bash +.venv/bin/pytest tests/test_navigator_safety.py tests/test_eval_runner.py -q +``` + +Expected: all tests pass. + +## Task 2: Make Observation Selection Structured + +**Files:** + +- Modify: `figment/prompt_builder.py` +- Modify: `figment/observation_targets.py` +- Modify: `scripts/run_eval.py` +- Test: `tests/test_prompt_builder_contract.py` +- Test: `tests/test_eval_runner.py` + +- [ ] **Step 1: Add a failing prompt contract test** + +Assert the prompt includes stable observation IDs: + +```python +def test_prompt_includes_required_observation_id_table(): + prompt = build_navigation_prompt(...) + assert "selected_required_observation_ids" in prompt.user_message + assert "CHEST-PAIN-ESCALATION-v1::required_observation::1" in prompt.user_message + assert "Choose required observation IDs before writing observation text" in prompt.user_message +``` + +- [ ] **Step 2: Add selected IDs to the model JSON schema** + +In the prompt skeleton, include: + +```json +"selected_required_observation_ids": [] +``` + +Instruction text should say: + +```text +Select the required observation IDs that matter for the cited source cards. Then write short responder-facing phrases for missing_info_to_collect and next_observations_to_collect using those IDs. +``` + +- [ ] **Step 3: Validate selected IDs before stripping** + +In `scripts/run_eval.py`, keep the current trace-only behavior but make the scoring path explicit: + +```python +model_selected_required_observation_ids = _string_list(raw_output.get("selected_required_observation_ids")) +invalid_selected_required_observation_ids = [ + observation_id + for observation_id in model_selected_required_observation_ids + if observation_id not in allowed_required_observation_ids +] +``` + +Strip the field from final user-facing output after validation/tracing. + +- [ ] **Step 4: Score model-owned observation coverage** + +Treat observation fields as model-owned when: + +- The selected IDs are valid. +- Every cited non-exempt clinical card has at least one selected required-observation ID. +- The natural-language arrays contain the display text or accepted synonym for those selected IDs. + +Keep deterministic fills as `deterministic_fallback`. + +- [ ] **Step 5: Run tests** + +Run: + +```bash +.venv/bin/pytest tests/test_prompt_builder_contract.py tests/test_eval_runner.py -q +``` + +Expected: prompt contract and trace/scoring behavior pass. + +## Task 3: Add Focused Source-Card Repair + +**Files:** + +- Modify: `scripts/run_eval.py` +- Modify: existing focused repair helper code used by `scripts/run_eval.py` +- Test: `tests/test_focused_repair.py` + +- [ ] **Step 1: Add a failing repair-scope test** + +Use failures like: + +```python +failures = [ + "fired rule card STROKE-SIGNS-v1 is not cited in source_cards", + "candidate pathway STROKE-SIGNS-v1 is not cited in source_cards", +] +``` + +Assert the selected scope is `citations_and_pathways` and the fields are: + +```python +("source_cards", "candidate_protocol_pathways") +``` + +- [ ] **Step 2: Require focused repair to preserve mandatory source cards** + +The repair prompt must include: + +```text +Mandatory source cards: STROKE-SIGNS-v1, SAFETY-BOUNDARIES-v1, REFERRAL-SBAR-v1 +Return exactly these top-level keys: source_cards, candidate_protocol_pathways. +Do not remove any mandatory source card. +``` + +- [ ] **Step 3: Reject repair outputs missing fired cards** + +After repair: + +```python +for card_id in mandatory_source_card_ids: + if card_id not in _string_list(repair_output.get("source_cards")): + repair_validation = {"passed": False, "failures": [f"repair omitted mandatory source card {card_id}"]} +``` + +- [ ] **Step 4: Run tests** + +Run: + +```bash +.venv/bin/pytest tests/test_focused_repair.py -q +``` + +Expected: all focused repair tests pass. + +## Task 4: Generate V5 Focused Corpus + +**Files:** + +- Create: `scripts/generate_v5_full_corpus.py` +- Modify: `scripts/generate_finetune_data.py` +- Modify: `scripts/verify_finetune_harness_alignment.py` +- Test: `tests/test_finetune_v5_data_plan.py` + +- [ ] **Step 1: Add corpus wrapper defaults** + +Create `scripts/generate_v5_full_corpus.py` with these defaults: + +```python +DEFAULT_OUTPUT_VERSION = "figment_sft_v5" +DEFAULT_COUNTS = { + "sbar_observation_ownership": 350, + "required_observation_id_selection": 250, + "source_card_invariant": 150, + "noisy_field_audio_style": 100, + "general_regression": 250, +} +``` + +- [ ] **Step 2: Add v5 metadata to every row** + +Each row must include metadata like: + +```json +{ + "dataset_version": "figment_sft_v5", + "training_focus": "sbar_observation_ownership", + "excluded_eval_case_ids": ["field_workflow_holdout_v1-000054", "field_workflow_holdout_v1-000099"], + "must_include_source_cards": ["REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1"], + "must_include_selected_required_observation_ids": ["..."] +} +``` + +Use v4 failures as pattern templates only. Do not train on copied holdout case text. + +- [ ] **Step 3: Add validator checks** + +`verify_finetune_harness_alignment.py` must reject any v5 row when: + +- A fired rule card is absent from `source_cards`. +- `selected_required_observation_ids` is empty for cited clinical cards with required observations. +- `REFERRAL-SBAR-v1` rows lack a complete SBAR object. +- Observation arrays are generic phrases like `repeat vitals`, `monitor closely`, or `ask anything else`. + +- [ ] **Step 4: Run corpus tests** + +Run: + +```bash +.venv/bin/pytest tests/test_finetune_v5_data_plan.py -q +``` + +Expected: v5 row metadata and validator rejection tests pass. + +## Task 5: Train V5 As A Focused Continuation + +**Files:** + +- Modify: `modal/finetune_figment_nemotron.py` +- Modify: `docs/local_4b_v5_training_plan.md` + +- [ ] **Step 1: Verify v5 dataset locally** + +Run: + +```bash +PYTHONPATH=. .venv/bin/python scripts/generate_v5_full_corpus.py +PYTHONPATH=. .venv/bin/python scripts/verify_finetune_harness_alignment.py \ + --dataset data/finetune/figment_sft_v5.jsonl \ + --case-specs data/finetune/figment_sft_v5_case_specs.jsonl +``` + +Expected: + +- At least `1100` accepted rows. +- `0` copied holdout rows. +- `0` source-card invariant violations. +- `0` empty selected-observation-ID violations. + +Current checkpoint: + +- Full `1100/1100` navigator rows are complete in shards `0-21`. +- Final corpus is verified and staged for Modal: + +```bash +PYTHONPATH=. .venv/bin/python scripts/verify_finetune_harness_alignment.py \ + --dataset data/finetune/figment_sft_v5.jsonl \ + --case-specs data/finetune/figment_sft_v5_case_specs.jsonl +``` + +- [x] **Step 2: Smoke train on Modal** + +Run the existing Modal trainer with: + +```bash +.venv/bin/modal run modal/finetune_figment_nemotron.py \ + --dataset-version figment_sft_v5 \ + --output-name figment-sft-v5-lora-smoke \ + --max-steps 20 +``` + +Expected: + +- Training starts. +- Loss is finite. +- Adapter artifacts are written. + +Actual: + +- Fresh smoke and resume-from-v4 smoke both completed with finite losses. +- Resume smoke wrote `/checkpoints/figment_sft_v5/figment-sft-v5-lora-resume-smoke`. + +- [x] **Step 3: Launch full detached training** + +Run: + +```bash +.venv/bin/modal run --detach modal/finetune_figment_nemotron.py \ + --dataset-version figment_sft_v5 \ + --output-name figment-sft-v5-lora +``` + +Record: + +- Modal app ID. +- Function call ID. +- Dashboard URL. +- Expected artifact path in `figment-checkpoints`. + +Actual: + +- App ID: `ap-AtxsW6TXtHhD1hIrt6da8s` +- Function call ID: `fc-01KTVEZF0JGJSFY7DVFMKVRFP1` +- Dashboard URL: `https://modal.com/id/fc-01KTVEZF0JGJSFY7DVFMKVRFP1` +- Expected artifact path: `/checkpoints/figment_sft_v5/figment-sft-v5-lora` +- Runtime GPU: `NVIDIA H100 80GB HBM3` + +- [ ] **Step 4: Merge and convert** + +After completion: + +```bash +.venv/bin/modal run modal/finetune_figment_nemotron.py \ + --dataset-version figment_sft_v5 \ + --output-name figment-sft-v5-lora \ + --merge-only + +.venv/bin/python tools/llama.cpp/convert_hf_to_gguf.py \ + artifacts/modal_checkpoints/figment-sft-v5-lora-merged-bf16 \ + --outfile artifacts/modal_checkpoints/figment-sft-v5-lora-merged-bf16.gguf \ + --outtype bf16 +``` + +- [ ] **Step 5: Run full local eval** + +Run the full 150-case holdout: + +```bash +/opt/homebrew/bin/llama-server \ + -m artifacts/modal_checkpoints/figment-sft-v5-lora-merged-bf16.gguf \ + --ctx-size 16384 \ + --host 127.0.0.1 \ + --port 8001 \ + --alias nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16 \ + --parallel 1 \ + --temp 0 \ + --top-p 1 \ + --reasoning off +``` + +Then: + +```bash +PYTHON_DOTENV_DISABLED=true \ +FIGMENT_MODEL_TIMEOUT_SECONDS=180 \ +LOCAL_GGUF_PATH=artifacts/modal_checkpoints/figment-sft-v5-lora-merged-bf16.gguf \ +.venv/bin/python scripts/run_local_4b_evidence.py \ + --base-url http://127.0.0.1:8001/v1 \ + --timeout-seconds 180 \ + --force-eval \ + --cases data/eval/field_workflow_holdout_v1.jsonl \ + --output-dir traces/local_4b_finetuned_v5_field_holdout_$(date -u +%Y%m%dT%H%M%SZ) +``` + +Expected: v5 meets the acceptance gates above. + +## Task 6: Decide Whether V5 Is Submission-Worthy + +**Files:** + +- Modify: `docs/local_4b_v5_training_plan.md` +- Optional modify: `docs/figment-build-small-lessons-draft.md` + +- [ ] **Step 1: Compare v4 and v5** + +Create a table with: + +- strict competence, +- final validation, +- expected labels, +- fallback uses, +- `REFERRAL-SBAR-v1` strict competence, +- `missing_info_to_collect` model ownership, +- `next_observations_to_collect` model ownership, +- hard source-card failures. + +- [ ] **Step 2: Make the call** + +If v5 clears gates, use v5 as the local fine-tuned model for submission evidence. + +If v5 improves observation ownership but misses `>=125/150`, keep v4 as the stable submission model and report v5 as a targeted experiment unless there is enough time for a v5.1 focused continuation. + +If v5 regresses red flags, urgency, forbidden behavior, or final validation, discard it for demo use and keep v4. + +## Implementation Order + +1. Task 1: fired-rule source-card invariant. +2. Task 2: structured observation selection. +3. Task 3: focused citation repair. +4. Re-run the current v4 model on the 150-case holdout to measure scaffold-only improvement. +5. Task 4: v5 corpus generation. +6. Task 5: v5 training, merge, GGUF conversion, full eval. +7. Task 6: submission decision. + +## Expected Outcome + +The most likely improvement path is: + +- Final validation: `148/150` -> `150/150`. +- Strict competence: `109/150` -> `125-135/150`. +- `REFERRAL-SBAR-v1`: `0/27` -> `20+/27`. +- Observation fields: `109/150` model-owned -> `140+/150` model-owned. +- Fallbacks: `2` -> `0-1`. + +The project should still describe the model honestly: v5 is not meant to be a general medical assistant. It is meant to be better at the bounded Figment job: faster intake completion, visible escalation cues, grounded protocol-card citation, and concise SBAR handoff support for rural clinic or disaster first-response medics. diff --git a/docs/local_4b_v6_training_plan.md b/docs/local_4b_v6_training_plan.md new file mode 100644 index 0000000000000000000000000000000000000000..48f847f0a8ce11269d8c1a408a4a7cdaf3d6e6ee --- /dev/null +++ b/docs/local_4b_v6_training_plan.md @@ -0,0 +1,512 @@ +# Figment Local 4B V6 Training Plan + +> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking. + +**Goal:** Train a v6 local 4B adapter that makes required-observation planning model-owned instead of scaffold-authored, while preserving the v5 safety, source-card, SBAR, and validation behavior. + +**Architecture:** Reuse v3-v5 rows as filtered replay, then add a focused v6 delta dataset for required-observation ownership inside the exact Figment harness prompt shape. Keep deterministic scaffolding as the product safety layer, but make the model reliably emit valid `selected_required_observation_ids`, `missing_info_to_collect`, and `next_observations_to_collect` before the scaffold patches them. + +**Tech Stack:** Python, JSONL SFT corpora, Figment eval harness, OpenRouter/NVIDIA teacher model, Modal LoRA SFT, H100/L40S GPU training, `llama.cpp`/GGUF evaluation, pytest. + +--- + +## Current Evidence + +Primary v5 eval trace: + +- `traces/figment_sft_v5_field_workflow_holdout_modal_gpu_20260611_h100_gguf/local_4b_eval.jsonl` +- `traces/figment_sft_v5_field_workflow_holdout_modal_gpu_20260611_h100_gguf/eval_summary.json` +- `traces/figment_sft_v5_field_workflow_holdout_modal_gpu_20260611_h100_gguf/modal_eval_manifest.json` + +Observed v5 result: + +- `150/150` final harness validation. +- `150/150` expected-label success. +- `0` global/canned fallback uses. +- `0` unsupported handoff facts. +- `1648/1950` model-visible fields retained, or `84.5%`. +- Only `2/150` configured-model outputs passed without deterministic field-level patching. +- Deterministic field patches appeared in `148/150` cases, primarily: + - `missing_info_to_collect`: `148/150` + - `next_observations_to_collect`: `148/150` + - `candidate_protocol_pathways`: `6/150` + +Diagnosis: + +V5 is not broadly unsafe or broadly confused. The product path is strong because the scaffold catches and repairs the weak field. The model-specific gap is narrow and important: the model does not reliably turn `required_observation_targets` into valid, responder-facing `missing_info_to_collect` and `next_observations_to_collect` fields. + +## Reuse Decision + +Do not fully regenerate v6 from scratch. + +Reuse previous datasets as replay because v3-v5 already contain valuable behavior: + +- v3 contains broad rural, disaster, low-resource, and field-workflow diversity. +- v4 contains stronger radio/SBAR/handoff usefulness examples. +- v5 contains source-card invariants, selected-observation-id scaffolding, and general regression examples. + +But do not blindly append old observation rows. The v5 result shows that the current observation examples were not sharp enough, were underweighted, or taught the wrong distinction between medic-owned observations and harness-owned metadata. + +Existing local corpora: + +- `data/finetune/figment_sft_v3.jsonl`: `3000` rows. +- `data/finetune/figment_sft_v4.jsonl`: `1650` rows. +- `data/finetune/figment_sft_v5.jsonl`: `1300` rows. +- `data/finetune/figment_sft_v5.jsonl` includes `242` `required_observation_id_selection` rows and `55` `focused_repair:missing_observations` rows. + +## Replay Audit Update + +The first v6 replay audit changed the corpus shape. + +Artifacts: + +- `scripts/build_v6_replay_corpus.py` +- `tests/test_v6_replay_selection.py` +- `data/finetune/figment_sft_v6_replay.jsonl` +- `data/finetune/figment_sft_v6_replay_manifest.json` + +Audit result: + +- `570` direct replay rows passed the v6 cleanliness policy. +- Selected replay rows by source: + - `figment_sft_v3`: `330` + - `figment_sft_v4`: `120` + - `figment_sft_v5`: `120` +- Selected replay rows by category: + - `focused_repair:handoff_note_sbar`: `233` + - `focused_repair:citations_and_pathways`: `163` + - `focused_repair:protocol_urgency`: `87` + - `focused_repair:schema`: `87` +- Selected replay rows by task type: + - `focused_repair`: `570` + +Interpretation: + +The usable replay pool is smaller than planned, and it contains no clean old full-navigator rows. Most old full-navigator rows teach at least one behavior v6 is supposed to stop: duplicated long `missing_info_to_collect` / `next_observations_to_collect` lists, harness metadata inside medic observation fields, or observation-focused rows without clean selected required-observation IDs. + +Rejected rows are still useful as negative/correction seeds, but not as positive replay targets. For v6 SFT, only the teacher-rewritten corrected output should be used as the assistant target. + +## V6 Dataset Shape + +Target total: `2000` rows. + +New v6 delta: `1430` rows. + +- `900` full navigator rows focused on required-observation ownership. +- `250` focused repair rows for `missing_info_to_collect` and `next_observations_to_collect`. +- `180` contrastive correction rows seeded from rejected old outputs, where the teacher rewrites the output into the v6 shape. +- `100` preservation rows for SBAR, source-card discipline, urgency floors, red flags, noisy intake, and low-resource constraints. + +Filtered replay: `570` rows. + +- `330` v3 focused-repair replay rows. +- `120` v4 focused-repair replay rows. +- `120` v5 focused-repair replay rows. + +Do not force the original `900` replay quota. If a row fails the v6 replay policy, either reject it outright or use it only as a seed for a teacher-generated correction example. + +Modal split target: + +- `1800` train rows. +- `200` validation rows. +- Preserve category balance in validation so v6 cannot hide observation failure in the train split. + +## V6 Gold Output Policy + +The teacher output must be aligned to the real harness prompt and schema. + +For full navigator rows, each accepted assistant output must: + +- emit complete navigator JSON in the current Figment shape; +- optionally emit trace-only `selected_required_observation_ids` for training, knowing the runtime strips it from final user-visible output; +- select required observation IDs only from `required_observation_targets`; +- include every metadata-required ID listed in `must_include_selected_required_observation_ids`; +- express each selected required observation ID as recognizable responder-facing text; +- keep `missing_info_to_collect` as the broader list of still-needed observations; +- keep `next_observations_to_collect` as the prioritized next 3-5 observations, not a copy of every missing item; +- avoid treating harness metadata as medic observations; +- preserve source-card discipline, urgency floors, red flags, SBAR grounding, and forbidden-behavior constraints. + +For focused repair rows, each accepted assistant output must: + +- return only `missing_info_to_collect` and `next_observations_to_collect`; +- repair validator-style missing-observation failures from the exact `build_focused_repair_prompts(...)` prompt shape; +- reference required observations by ID and display text; +- preserve valid existing clinical workflow content; +- avoid expanding into a full navigator answer. + +## V6 Observation Policy + +Reject any new or replay row that violates these rules. + +Hard rejects: + +- `missing_info_to_collect` and `next_observations_to_collect` are identical non-empty lists with more than three items. +- Observation fields include harness-owned metadata phrases such as: + - `source card IDs` + - `source protocol card IDs` + - `retrieved protocol card IDs` + - `deterministic rule results` + - `navigator validation result` + - `confirmed intake status` + - `manual correction status for audio-derived fields` +- `selected_required_observation_ids` is missing for a v6 full navigator row. +- Any selected required-observation ID is not in the provided `required_observation_targets`. +- Any ID in `must_include_selected_required_observation_ids` is absent from the assistant output. +- A selected required-observation ID has no matching responder-facing text in either observation field. +- Observation text gives diagnosis, medication, dosing, procedure, disposition, or autonomous routing instructions. +- The row overlaps the locked eval signatures from: + - `data/eval/field_workflow_holdout_v1.jsonl` + - `data/eval/adversarial_strict_cases.jsonl` + - `data/eval/comprehensive_hosted_cases.jsonl` + - `data/eval/initial_handwritten_cases.jsonl` + +Soft preferences: + +- `next_observations_to_collect` should usually be a prioritized subset of `missing_info_to_collect`. +- Prefer concrete field language: `count respiratory rate`, `measure blood pressure if cuff available`, `confirm bleeding amount`, `check current mental status`. +- Avoid generic filler: `monitor closely`, `collect more information`, `follow up`, `assess patient`. +- Preserve uncertainty explicitly when intake is unclear or conflicting. + +## Teacher Generation Strategy + +Use the same teacher route as v5 unless the primary NVIDIA endpoint is healthy: + +- Preferred teacher if available: `nvidia/nemotron-3-ultra-550b-a55b` +- Working fallback teacher: `nvidia/nemotron-3-ultra-550b-a55b:free` via OpenRouter + +Generate new v6 cases as near-neighbor-free variants, not copies of holdout cases. + +Each new case spec should include: + +- setting, +- responder constraints, +- confirmed intake facts, +- denied or absent symptoms, +- retrieved card set, +- fired deterministic rules, +- urgency floor, +- required observation targets, +- expected selected required-observation IDs, +- expected model-owned observation cue phrases, +- forbidden behavior. + +Failure classes to oversample: + +- missing required-observation IDs; +- invalid selected required-observation IDs; +- generic observation filler; +- duplicate missing/next observation lists; +- harness metadata incorrectly placed in observation fields; +- unknown observation target omitted from text; +- known observation incorrectly repeated as missing; +- treatment advice disguised as observation collection. + +## Implementation Tasks + +### Task 1: Summarize V5 Observation Failures + +**Files:** + +- Read: `traces/figment_sft_v5_field_workflow_holdout_modal_gpu_20260611_h100_gguf/local_4b_eval.jsonl` +- Create: `traces/figment_sft_v5_field_workflow_holdout_modal_gpu_20260611_h100_gguf/v6_observation_failure_summary.json` + +- [ ] Count deterministic patches by field. +- [ ] Count missing, invalid, and unused `selected_required_observation_ids`. +- [ ] Extract top required-observation target IDs that were scaffold-filled. +- [ ] Extract bad model phrasings that caused patching. +- [ ] Save a compact JSON summary for v6 corpus generation. + +Suggested command: + +```bash +PYTHONPATH=. .venv/bin/python scripts/summarize_v6_observation_failures.py \ + --eval-jsonl traces/figment_sft_v5_field_workflow_holdout_modal_gpu_20260611_h100_gguf/local_4b_eval.jsonl \ + --output traces/figment_sft_v5_field_workflow_holdout_modal_gpu_20260611_h100_gguf/v6_observation_failure_summary.json +``` + +Expected result: + +- `total_cases` is `150`. +- `missing_info_to_collect` deterministic patch count is near `148`. +- `next_observations_to_collect` deterministic patch count is near `148`. +- The summary names exact observation target IDs and phrase families to generate against. + +### Task 2: Add V6 Observation Filters + +**Files:** + +- Modify: `scripts/verify_finetune_harness_alignment.py` +- Modify: `scripts/generate_finetune_data.py` +- Test: `tests/test_finetune_v5_data_plan.py` +- Create: `tests/test_finetune_v6_data_plan.py` + +- [ ] Add a `uses_v6_observation_policy(dataset_version: str) -> bool` helper. +- [ ] Reject duplicate non-empty `missing_info_to_collect` and `next_observations_to_collect` lists with more than three items. +- [ ] Reject harness-owned metadata cues in observation fields. +- [ ] Reject missing or invalid `selected_required_observation_ids`. +- [ ] Reject rows where selected IDs are not visible as responder-facing text. +- [ ] Add tests for each reject reason. + +Suggested verification: + +```bash +PYTHONPATH=. .venv/bin/pytest tests/test_finetune_v6_data_plan.py tests/test_finetune_v5_data_plan.py -q +``` + +Expected result: + +- v5 tests still pass. +- v6 tests prove every hard reject is enforced. + +### Task 3: Build Filtered Replay Corpus + +**Files:** + +- Create: `scripts/build_v6_replay_corpus.py` +- Read: `data/finetune/figment_sft_v3.jsonl` +- Read: `data/finetune/figment_sft_v4.jsonl` +- Read: `data/finetune/figment_sft_v5.jsonl` +- Create: `data/finetune/figment_sft_v6_replay.jsonl` +- Create: `data/finetune/figment_sft_v6_replay_manifest.json` + +- [x] Audit v3-v5 rows with the v6 replay policy. +- [x] Select only rows that avoid duplicate long observation lists and harness metadata in observation fields. +- [x] Preserve only clean direct replay rows instead of filling quota with bad rows. +- [x] Run every candidate through the v6 observation policy. +- [x] Preserve original row metadata with `source_dataset_version`. +- [x] Add `replay_reason` metadata to each retained row. +- [x] Save a manifest with source counts, rejected counts, and SHA256. + +Suggested command: + +```bash +PYTHONPATH=. .venv/bin/python scripts/build_v6_replay_corpus.py \ + --input data/finetune/figment_sft_v5.jsonl \ + --input data/finetune/figment_sft_v4.jsonl \ + --input data/finetune/figment_sft_v3.jsonl \ + --output data/finetune/figment_sft_v6_replay.jsonl \ + --manifest data/finetune/figment_sft_v6_replay_manifest.json \ + --figment-sft-v5-target 450 \ + --figment-sft-v4-target 300 \ + --figment-sft-v3-target 150 +``` + +Expected result: + +- `data/finetune/figment_sft_v6_replay.jsonl` contains `570` clean direct replay rows. +- The manifest reports `0` v6 policy issues among retained rows. +- The manifest records replay shortages rather than filling the planned quota with bad rows. +- Selected rows contain `0` duplicate long missing/next observation lists. +- Selected rows contain `0` harness-metadata cue hits in assistant observation fields. + +### Task 4: Generate New V6 Delta Rows + +**Files:** + +- Modify: `scripts/generate_finetune_data.py` +- Create: `scripts/generate_v6_full_corpus.py` +- Create: `data/finetune/figment_sft_v6_delta.jsonl` +- Create: `data/finetune/figment_sft_v6_delta_case_specs.jsonl` +- Create: `data/finetune/figment_sft_v6_delta_manifest.json` + +- [ ] Add v6 failure classes to the case-spec scheduler. +- [ ] Oversample required-observation targets that v5 scaffold-filled. +- [ ] Use rejected old full-navigator rows as negative/correction seeds, not as positive SFT targets. +- [ ] Ask the teacher for full navigator output in the real prompt shape. +- [ ] Ask the teacher for focused repair output in the real repair prompt shape. +- [ ] Ask the teacher to rewrite rejected prior outputs into clean v6 full-navigator targets. +- [ ] Reject rows that fail v6 observation policy. +- [ ] Reject rows that fail existing harness alignment checks. +- [ ] Save accepted rows and case specs with anti-overfit signatures enabled. + +Suggested smoke: + +```bash +PYTHONPATH=. .venv/bin/python scripts/generate_v6_full_corpus.py \ + --new-delta-count 10 \ + --repair-count 3 \ + --correction-count 2 \ + --parallelism 1 \ + --output /tmp/figment_sft_v6_delta_smoke.jsonl \ + --case-specs /tmp/figment_sft_v6_delta_smoke_case_specs.jsonl \ + --manifest /tmp/figment_sft_v6_delta_smoke_manifest.json +``` + +Expected smoke result: + +- `15` accepted rows. +- `0` verifier issues. +- At least one accepted row for duplicate-list correction. +- At least one accepted row for harness-owned metadata exclusion. + +Suggested full generation: + +```bash +PYTHONPATH=. .venv/bin/python scripts/generate_v6_full_corpus.py \ + --new-delta-count 1000 \ + --repair-count 250 \ + --correction-count 180 \ + --parallelism 4 \ + --teacher-error-retries 3 \ + --teacher-error-sleep-seconds 10 \ + --output data/finetune/figment_sft_v6_delta.jsonl \ + --case-specs data/finetune/figment_sft_v6_delta_case_specs.jsonl \ + --manifest data/finetune/figment_sft_v6_delta_manifest.json +``` + +Expected full result: + +- `1430` accepted delta rows. +- Delta includes `900` required-observation full-navigator rows, `250` focused missing-observation repair rows, `180` teacher-rewritten correction rows, and `100` preservation rows. +- `0` verifier issues. +- Delta manifest records category counts and rejected row reasons. + +### Task 5: Merge, Verify, And Split V6 + +**Files:** + +- Create: `data/finetune/figment_sft_v6.jsonl` +- Create: `data/finetune/figment_sft_v6_manifest.json` +- Create: `data/finetune/modal/figment_sft_v6/train.jsonl` +- Create: `data/finetune/modal/figment_sft_v6/validation.jsonl` +- Create: `data/finetune/modal/figment_sft_v6/manifest.json` + +- [ ] Merge `figment_sft_v6_delta.jsonl` and `figment_sft_v6_replay.jsonl`. +- [ ] Shuffle deterministically with a fixed seed. +- [ ] Verify the full merged dataset. +- [ ] Split into `1800` train rows and `200` validation rows. +- [ ] Verify train and validation SHA256 hashes in the Modal manifest. + +Suggested commands: + +```bash +PYTHONPATH=. .venv/bin/python scripts/merge_v6_training_corpus.py \ + --delta data/finetune/figment_sft_v6_delta.jsonl \ + --replay data/finetune/figment_sft_v6_replay.jsonl \ + --output data/finetune/figment_sft_v6.jsonl \ + --manifest data/finetune/figment_sft_v6_manifest.json \ + --modal-output-dir data/finetune/modal/figment_sft_v6 \ + --train-count 1800 \ + --validation-count 200 + +PYTHONPATH=. .venv/bin/python scripts/verify_finetune_harness_alignment.py \ + --dataset data/finetune/figment_sft_v6.jsonl \ + --case-specs data/finetune/figment_sft_v6_delta_case_specs.jsonl +``` + +Expected result: + +- Full dataset has `2000` rows. +- Full dataset is `1430` new/corrected delta rows plus `570` clean direct replay rows. +- Modal train split has `1800` rows. +- Modal validation split has `200` rows. +- Verifier reports `issue_count=0`. + +### Task 6: Train V6 On Modal + +**Files:** + +- Use: `modal/finetune_figment_nemotron.py` +- Use: `data/finetune/modal/figment_sft_v6/train.jsonl` +- Use: `data/finetune/modal/figment_sft_v6/validation.jsonl` +- Output: `figment-checkpoints:/figment_sft_v6/figment-sft-v6-lora` + +- [ ] Run a short smoke training job. +- [ ] Verify finite train and eval loss. +- [ ] Verify adapter artifacts. +- [ ] Launch full detached training. +- [ ] Prefer continuation from the v5 adapter with a lower learning rate. +- [ ] Keep a fallback option to resume from v4 if v5 continuation shows observation overfitting or safety regression in smoke eval. + +Suggested smoke: + +```bash +PYTHONPATH=. .venv/bin/modal run modal/finetune_figment_nemotron.py::train \ + --dataset-version figment_sft_v6 \ + --output-name figment-sft-v6-lora-smoke \ + --max-steps 20 \ + --resume-adapter-name figment-sft-v5-lora \ + --resume-adapter-dataset-version figment_sft_v5 +``` + +Suggested full detached run: + +```bash +PYTHONPATH=. .venv/bin/modal run --detach modal/finetune_figment_nemotron.py::train \ + --dataset-version figment_sft_v6 \ + --output-name figment-sft-v6-lora \ + --resume-adapter-name figment-sft-v5-lora \ + --resume-adapter-dataset-version figment_sft_v5 +``` + +Expected result: + +- Adapter artifacts exist under `/checkpoints/figment_sft_v6/figment-sft-v6-lora`. +- `adapter_model.safetensors`, `adapter_config.json`, tokenizer files, `chat_template.jinja`, and `figment_training_manifest.json` are present. + +### Task 7: Merge, Convert, And Evaluate V6 + +**Files:** + +- Use: `modal/eval_figment_nemotron.py` +- Use: `data/eval/field_workflow_holdout_v1.jsonl` +- Output: `traces/figment_sft_v6_field_workflow_holdout_modal_gpu_/` + +- [ ] Merge the v6 adapter into BF16 weights. +- [ ] Convert to GGUF if the eval path requires it. +- [ ] Run the full `150`-case `field_workflow_holdout_v1` suite. +- [ ] Save JSONL traces, summaries, route smoke, endpoint metadata, and manifest. +- [ ] Verify result count is exactly `150`. +- [ ] Compare field provenance against v5. + +Suggested eval: + +```bash +PYTHONPATH=. .venv/bin/modal run modal/eval_figment_nemotron.py::run_batch_eval \ + --dataset-version figment_sft_v6 \ + --model-artifact figment-checkpoints:/figment_sft_v6/figment-sft-v6-lora-merged-bf16 \ + --cases data/eval/field_workflow_holdout_v1.jsonl \ + --output-name figment_sft_v6_field_workflow_holdout +``` + +Expected result: + +- Eval JSONL contains `150` records. +- Summary includes raw, repair, fallback, field-provenance, latency, and trace-hash counts. + +## Acceptance Gates + +V6 is accepted only if it beats v5 on model ownership without losing safety. + +Required: + +- `150/150` final validation successes. +- `150/150` trace hashes present. +- `0` global/canned fallback uses. +- `0` unsupported handoff facts. +- `0` invalid selected required-observation IDs. +- `missing_info_to_collect` model-owned in `>=140/150`. +- `next_observations_to_collect` model-owned in `>=140/150`. +- Deterministic patches for `missing_info_to_collect` are `<=10/150`. +- Deterministic patches for `next_observations_to_collect` are `<=10/150`. +- `raw_configured_model_successes >=125/150`. +- No regression in red flags, urgency floors, source-card discipline, or SBAR handoff grounding. + +Nice to have: + +- Mean latency stays below v5 by avoiding repair calls. +- Field retention improves from v5's `84.5%` to `>=93%`. +- `candidate_protocol_pathways` deterministic patches remain `<=6/150`. + +## Stop Conditions + +Do not proceed to full training if: + +- v6 smoke rows fail harness verification; +- the replay builder cannot produce more than `570` clean rows without weakening filters and the plan still assumes old direct replay can fill the gap; +- teacher output repeatedly treats harness metadata as medic observation text; +- smoke training shows non-finite loss; +- smoke eval regresses safety, source cards, or unsupported handoff facts. + +If those happen, fix the v6 data policy or generator first. Do not solve this by broadening the corpus or relaxing the eval. diff --git a/docs/local_4b_v7_training_corpora_plan.md b/docs/local_4b_v7_training_corpora_plan.md new file mode 100644 index 0000000000000000000000000000000000000000..5055208d783b3ef40e85535cdb8573d4175236df --- /dev/null +++ b/docs/local_4b_v7_training_corpora_plan.md @@ -0,0 +1,957 @@ +# Figment Local 4B V7 Training Corpora Implementation Plan + +> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking. + +**Goal:** Build a v7 SFT corpus that keeps v6's large reduction in scaffold dependence while restoring source-card closure and improving the model's native ability to operate inside the Figment field-workflow harness. + +**Architecture:** Treat v6 as the behavior anchor, reuse only audited v6 and historical replay rows, and add a focused v7 delta for source-card closure, joint source-card plus observation ownership, and distractor-card resistance. The corpus remains aligned to the exact navigator and focused-repair prompt shapes used by the harness, with verifier gates that reject rows teaching deterministic patch artifacts or eval leakage. + +**Tech Stack:** Python, JSONL SFT corpora, Figment eval harness, OpenRouter/NVIDIA Nemotron teacher, Modal LoRA SFT, H100 training, `llama.cpp`/GGUF evaluation, pytest. + +--- + +## Current Evidence + +Primary v6 eval trace: + +- `traces/figment_sft_v6_field_workflow_holdout_modal_gpu_20260611_h100_gguf/local_4b_eval.jsonl` +- `traces/figment_sft_v6_field_workflow_holdout_modal_gpu_20260611_h100_gguf/eval_summary.json` +- `traces/figment_sft_v6_field_workflow_holdout_modal_gpu_20260611_h100_gguf/summary.json` + +Observed v6 result: + +- `142/150` configured-model competence successes. +- `150/150` final validation successes. +- `146/150` expected-label successes. +- `0` fallback uses. +- `21` deterministic field patches across `1950` scored visible fields. +- Field provenance: + - `source_cards`: `144/150` model raw, `6/150` deterministic fallback. + - `missing_info_to_collect`: `143/150` model raw, `7/150` deterministic fallback. + - `next_observations_to_collect`: `143/150` model raw, `7/150` deterministic fallback. + - `candidate_protocol_pathways`: `149/150` model raw, `1/150` deterministic fallback. + +Primary v5 comparison trace: + +- `traces/figment_sft_v5_field_workflow_holdout_modal_gpu_20260611_h100_gguf/local_4b_eval.jsonl` +- `traces/figment_sft_v5_field_workflow_holdout_modal_gpu_20260611_h100_gguf/eval_summary.json` + +Observed v5 comparison: + +- `2/150` configured-model competence successes. +- `150/150` final validation successes. +- `150/150` expected-label successes. +- `0` fallback uses. +- `302` deterministic field patches. + +Interpretation: + +V6 is the right base. It made the model far less scaffold-dependent than v5 while preserving final safety. The v7 corpus should not revert to the v5 shape, where final outputs looked good because scaffolding was doing too much. The v7 target is to keep v6's model-owned observation behavior and close the small source-card exactness gap. + +## V6 Failure Shape + +Configured-model competence failures: + +- `field_workflow_holdout_v1-000019` +- `field_workflow_holdout_v1-000050` +- `field_workflow_holdout_v1-000055` +- `field_workflow_holdout_v1-000067` +- `field_workflow_holdout_v1-000078` +- `field_workflow_holdout_v1-000091` +- `field_workflow_holdout_v1-000099` +- `field_workflow_holdout_v1-000115` + +Expected-label failures: + +- `field_workflow_holdout_v1-000067` +- `field_workflow_holdout_v1-000091` +- `field_workflow_holdout_v1-000099` +- `field_workflow_holdout_v1-000115` + +Source-card misses inside expected-label failures: + +- `field_workflow_holdout_v1-000067`: missing `REFERRAL-SBAR-v1` and `SAFETY-BOUNDARIES-v1`; actual source cards were `PREG-DANGER-SIGNS-v1`, `CHEST-PAIN-ESCALATION-v1`, and `FEVER-RED-FLAGS-v1`. +- `field_workflow_holdout_v1-000091`: missing `REFERRAL-SBAR-v1` and `SAFETY-BOUNDARIES-v1`; actual source cards were `PREG-DANGER-SIGNS-v1`, `CHEST-PAIN-ESCALATION-v1`, and `FEVER-RED-FLAGS-v1`. +- `field_workflow_holdout_v1-000099`: missing `SAFETY-BOUNDARIES-v1`; actual source cards were `PREG-DANGER-SIGNS-v1`, `CHEST-PAIN-ESCALATION-v1`, `FEVER-RED-FLAGS-v1`, and `REFERRAL-SBAR-v1`. +- `field_workflow_holdout_v1-000115`: missing `REFERRAL-SBAR-v1` and `SAFETY-BOUNDARIES-v1`; actual source cards were `PREG-DANGER-SIGNS-v1`, `CHEST-PAIN-ESCALATION-v1`, and `FEVER-RED-FLAGS-v1`. + +Patch fields across the eight competence failures: + +- `source_cards`: `6` +- `missing_info_to_collect`: `7` +- `next_observations_to_collect`: `7` +- `candidate_protocol_pathways`: `1` + +Diagnosis: + +The main v7 data need is not broad medical reasoning. It is harness-native closure behavior: + +- If the answer uses SBAR handoff structure, cite `REFERRAL-SBAR-v1`. +- If the answer emits safety boundaries, forbidden-action constraints, or protocol-only disclaimers, cite `SAFETY-BOUNDARIES-v1`. +- If multiple clinical protocol cards are relevant, do not let the support cards disappear. +- If retrieval includes distractor protocol cards, cite the mandatory support cards without over-citing irrelevant clinical cards. +- Preserve v6's model-owned observation fields while improving source-card closure in the same output. + +## Existing Corpora + +Canonical local files: + +- `data/finetune/figment_sft_v3.jsonl`: `3000` rows. +- `data/finetune/figment_sft_v4.jsonl`: `1650` rows. +- `data/finetune/figment_sft_v5.jsonl`: `1300` rows. +- `data/finetune/figment_sft_v6_delta.jsonl`: `1430` rows. +- `data/finetune/figment_sft_v6_replay.jsonl`: `570` rows. +- `data/finetune/figment_sft_v6.jsonl`: `2000` rows. + +V6 merged corpus shape: + +- `1430` v6 delta rows. +- `570` audited historical replay rows. +- Replay source counts: + - `figment_sft_v3`: `330` + - `figment_sft_v4`: `120` + - `figment_sft_v5`: `120` +- Task type counts: + - `navigator_full`: `1180` + - `focused_repair`: `820` +- V6 verifier result: `2000` rows, `1413` case specs, `0` issues. + +V6 category counts: + +- `required_observation_ownership`: `879` +- `observation_correction`: `218` +- `v6_preservation`: `83` +- `focused_repair:missing_observations`: `250` +- `focused_repair:handoff_note_sbar`: `233` +- `focused_repair:citations_and_pathways`: `163` +- `focused_repair:protocol_urgency`: `87` +- `focused_repair:schema`: `87` + +## Reuse Decision + +Do not fully regenerate v7 from scratch. + +Reuse v6 heavily because v6 is the first adapter that made model-owned harness behavior plausible. Blindly adding older corpora would risk reintroducing v5's failure mode, where the output passed only because deterministic scaffolding repaired hundreds of fields. + +Safe reuse: + +- Reuse all `570` rows from `data/finetune/figment_sft_v6_replay.jsonl`. +- Reuse all `1430` rows from `data/finetune/figment_sft_v6_delta.jsonl`. +- Prefer v6 delta rows that already passed source-card, observation, SBAR, urgency, schema, and forbidden-behavior checks. +- Keep category balance so v7 does not overfit to source cards and forget required-observation ownership. + +Replay audit update: + +- `scripts/build_v7_replay_corpus.py` selected `2000` reusable rows. +- Selected by source bucket: + - `figment_sft_v6_delta`: `1430` + - `figment_sft_v6_replay`: `570` +- Selected by task type: + - `navigator_full`: `1180` + - `focused_repair`: `820` +- Selected by category: + - `required_observation_ownership`: `879` + - `observation_correction`: `218` + - `v6_preservation`: `83` + - `focused_repair:missing_observations`: `250` + - `focused_repair:handoff_note_sbar`: `233` + - `focused_repair:citations_and_pathways`: `163` + - `focused_repair:protocol_urgency`: `87` + - `focused_repair:schema`: `87` + +Interpretation: + +The plan no longer needs `1200` newly generated rows. All v6 anchor rows pass the v7 replay gate, so v7 should preserve the full v6 behavior base and add a smaller, sharper source-card closure delta. + +Selective historical reuse: + +- Do not directly append v3, v4, or v5 rows beyond the already audited v6 replay rows. +- If more historical diversity is needed, run the v7 replay selector against v3-v6 and select only rows passing the v7 policy. +- Rejected v3-v5 rows may be used as teacher rewrite seeds, not as positive assistant targets. + +Hard non-reuse: + +- Do not train on exact `field_workflow_holdout_v1` examples as assistant targets. +- Do not use rows where `source_cards` were correct only after deterministic patching. +- Do not use rows with harness-owned metadata in responder observation fields. +- Do not use rows with duplicated long `missing_info_to_collect` and `next_observations_to_collect`. +- Do not use rows that teach arbitrary over-citation of every retrieved card. + +## V7 Target Corpus Shape + +Target total: `2800` rows. + +Reused anchor rows: `2000`. + +- `570` rows from `data/finetune/figment_sft_v6_replay.jsonl`. +- `1430` rows from `data/finetune/figment_sft_v6_delta.jsonl`. + +New v7 delta rows: `800`. + +- `240` `source_card_closure` navigator rows. +- `160` `focused_repair:source_card_closure` rows. +- `140` `observation_source_joint` navigator rows. +- `100` `distractor_card_resistance` navigator rows. +- `80` `sbar_source_coupling` navigator rows. +- `50` `source_card_negative_correction` focused-repair rows. +- `30` `observation_patch_repair` focused-repair rows. + +Final v7 task type target: + +- `navigator_full`: about `1740` rows. +- `focused_repair`: about `1060` rows. + +Final v7 source target: + +- `v6_delta_reuse`: `1430` +- `v6_replay_reuse`: `570` +- `v7_delta`: `800` + +## New Data Category Definitions + +### `source_card_closure` + +Purpose: Teach the model to include mandatory support cards in `source_cards` when the output relies on their content. + +Each row must include: + +- at least one clinical target card; +- `SAFETY-BOUNDARIES-v1` whenever `safety_boundary` or `do_not_do` uses protocol-only, no-orders, no-diagnosis, no-treatment, or local-protocol language; +- `REFERRAL-SBAR-v1` whenever `handoff_note_sbar` is present and actionable; +- at least one multi-card scenario where clinical cards compete for attention; +- complete source-card list in the assistant output before any deterministic repair. + +Oversample source-card combinations matching the v6 misses: + +- `PREG-DANGER-SIGNS-v1` plus `CHEST-PAIN-ESCALATION-v1` plus `FEVER-RED-FLAGS-v1` plus `SAFETY-BOUNDARIES-v1` plus `REFERRAL-SBAR-v1`. +- The same clinical triad plus only one support-card distractor, requiring the teacher to add the missing support card. +- Clinical card plus `SAFETY-BOUNDARIES-v1` plus `REFERRAL-SBAR-v1`, with irrelevant retrieved distractors excluded. + +### `focused_repair:source_card_closure` + +Purpose: Teach minimal repair behavior for source-card exactness without requiring a full navigator regeneration. + +Prompt shape: + +- Use the same focused-repair path as `focused_repair:citations_and_pathways`. +- Input includes a flawed model output whose `source_cards` omit one or both support cards. +- Assistant target returns only the repaired fields requested by the focused-repair prompt. + +Each accepted row must: + +- add missing mandatory source cards; +- preserve valid existing clinical source cards; +- avoid adding irrelevant retrieved cards; +- preserve candidate pathway card IDs when they are already correct; +- avoid changing urgency, handoff, observation, or safety text unless the focused-repair scope asks for it. + +### `observation_source_joint` + +Purpose: Preserve v6's observation gains while teaching source-card closure in the same full output. + +Each row must require: + +- valid `selected_required_observation_ids`; +- responder-facing text for every selected ID; +- non-identical `missing_info_to_collect` and `next_observations_to_collect`; +- complete `source_cards` including relevant clinical and support cards; +- SBAR handoff that cites or depends on `REFERRAL-SBAR-v1`; +- safety boundary that cites or depends on `SAFETY-BOUNDARIES-v1`. + +### `distractor_card_resistance` + +Purpose: Prevent v7 from solving closure by over-citing every retrieved card. + +Each row must include: + +- retrieved cards containing at least one irrelevant clinical protocol; +- expected source cards that include the target clinical card and mandatory support cards; +- explicit exclusion of irrelevant retrieved card IDs from `source_cards`; +- normal final validation behavior. + +The verifier must reject rows where the teacher adds every retrieved card to `source_cards` without justification. + +### `sbar_source_coupling` + +Purpose: Make the SBAR card load-bearing when the answer includes SBAR structure. + +Each row must include: + +- an SBAR handoff with situation, background, objective assessment observations, and request; +- `REFERRAL-SBAR-v1` in `source_cards`; +- no unsupported facts in the SBAR assessment; +- no treatment orders, dosing, or autonomous disposition. + +### `source_card_negative_correction` + +Purpose: Use bad source-card outputs as correction seeds. + +Input flaws to seed: + +- missing `SAFETY-BOUNDARIES-v1`; +- missing `REFERRAL-SBAR-v1`; +- missing both support cards; +- over-citing unrelated clinical cards; +- replacing the target clinical card with a support card; +- placing source-card IDs in `missing_info_to_collect` or `next_observations_to_collect`. + +Assistant target: + +- a corrected focused-repair JSON answer that fixes source-card fields only. + +### `observation_patch_repair` + +Purpose: Keep pressure on the remaining v6 observation patch cases without rebuilding the whole corpus around observations. + +Input flaws to seed: + +- missing selected required-observation IDs; +- selected IDs not visible in observation text; +- duplicate long missing and next observation lists; +- generic filler such as `monitor closely` as a standalone observation; +- known observations repeated as missing. + +Assistant target: + +- corrected observation fields in the exact focused-repair prompt shape. + +### `v7_preservation` + +Purpose: Guard against regressions in the behavior already working in v6. + +Rows should cover: + +- red-flag urgency floors; +- protocol-only safety boundaries; +- no diagnosis or treatment instructions; +- noisy/radio-style intake; +- rural clinic and disaster first-response constraints; +- short SBAR handoffs with objective observations only; +- target clinical card retained in both candidate pathways and source cards. + +## V7 Gold Output Policy + +For full navigator rows, accepted assistant output must: + +- emit complete navigator JSON in the current Figment shape; +- include valid `candidate_protocol_pathways`; +- include complete `source_cards` with all cards used by the output; +- include `SAFETY-BOUNDARIES-v1` when safety boundary or forbidden-action content is present; +- include `REFERRAL-SBAR-v1` when SBAR handoff structure is present; +- include the target protocol card in `source_cards`; +- include any fired deterministic rule card in `source_cards`; +- optionally include trace-only `selected_required_observation_ids`; +- select required observation IDs only from `required_observation_targets`; +- include every metadata-required ID listed in `must_include_selected_required_observation_ids`; +- express every selected required-observation ID as recognizable responder-facing text; +- keep `next_observations_to_collect` as a prioritized subset or near-subset of `missing_info_to_collect`, not a full copy; +- preserve protocol-only, no-treatment, no-diagnosis, and no-autonomous-disposition boundaries. + +For focused repair rows, accepted assistant output must: + +- return only the fields requested by the focused-repair prompt; +- repair the targeted failure; +- preserve valid existing fields; +- avoid expanding into a full navigator answer; +- avoid visible reasoning tags, teacher notes, or commentary. + +## V7 Replay Policy + +Use the v6 replay policy as the base and add source-card closure checks. + +Hard rejects: + +- Any row failing the existing v6 policy in `scripts/build_v6_replay_corpus.py`. +- Any row with `metadata.expected_label_score.all_expected_labels_passed == false`. +- Any row where `metadata.validation_result.passed == false`. +- Any row where source-card provenance says deterministic fallback authored `source_cards`. +- Any full navigator row with `handoff_note_sbar` present and `REFERRAL-SBAR-v1` absent from `source_cards`. +- Any full navigator row with safety-boundary text present and `SAFETY-BOUNDARIES-v1` absent from `source_cards`. +- Any full navigator row where the target protocol card is absent from `source_cards`. +- Any row that adds all retrieved cards when irrelevant distractors are marked in metadata. +- Any row overlapping locked eval signatures from: + - `data/eval/field_workflow_holdout_v1.jsonl` + - `data/eval/adversarial_strict_cases.jsonl` + - `data/eval/comprehensive_hosted_cases.jsonl` + - `data/eval/initial_handwritten_cases.jsonl` + +Soft preferences: + +- Prefer v6 rows where all scored fields were `model_raw`. +- Prefer rows with source-card lists of length `3` to `5`. +- Prefer multi-card cases with one target clinical card plus support cards. +- Prefer concise observation fields and short SBAR handoffs. +- Prefer rows with no deterministic patches in their originating eval metadata. + +## Teacher Generation Strategy + +Teacher model: + +- Primary: `nvidia/nemotron-3-ultra-550b-a55b:free` through the existing OpenRouter endpoint. +- Alternate: `nvidia/nemotron-3-ultra-550b-a55b` through the NVIDIA-compatible endpoint if quota and reliability are healthy. + +Teacher prompt requirements: + +- Build prompts through the existing Figment case/preparation path, not a generic clinical note format. +- Include the exact current navigator JSON schema. +- Include retrieved card IDs and card summaries. +- Include required-observation targets for full navigator rows. +- Include closure rules for `SAFETY-BOUNDARIES-v1` and `REFERRAL-SBAR-v1`. +- Include distractor-card instructions where relevant. +- Tell the teacher to produce only JSON. + +Generation must use near-neighbor variants of failures, not copied holdout cases. + +Variant knobs: + +- rural clinic versus disaster first-response setting; +- adult, pediatric, pregnant, fever, chest pain, respiratory distress, stroke, wound infection, and altered mental status presentations; +- partial vitals, noisy intake, radio-style handoff, missing transport availability, language uncertainty, and power/network constraints; +- retrieved card order permutations; +- support cards placed first, middle, or last in retrieval context; +- irrelevant clinical distractors included but not cited. + +## File Map + +Create: + +- `docs/local_4b_v7_training_corpora_plan.md`: this plan. +- `scripts/summarize_v7_corpus_needs.py`: extracts v6 failure IDs, source-card misses, deterministic patch fields, and source-card closure combinations. +- `scripts/build_v7_replay_corpus.py`: selects clean v6 and historical replay rows under the v7 policy. +- `scripts/generate_v7_full_corpus.py`: generates v7 delta rows, verifies them, and prepares Modal train/validation splits. +- `scripts/merge_v7_training_corpus.py`: merges v7 delta rows with v7 replay rows and writes manifest plus Modal split artifacts. +- `tests/test_finetune_v7_data_plan.py`: verifies v7 category counts, replay policy, closure rules, and wrapper defaults. +- `data/finetune/figment_sft_v7_replay.jsonl`: selected reusable rows. +- `data/finetune/figment_sft_v7_replay_manifest.json`: replay selection evidence. +- `data/finetune/figment_sft_v7_delta.jsonl`: newly generated v7 rows. +- `data/finetune/figment_sft_v7_delta_case_specs.jsonl`: case specs for new v7 navigator rows. +- `data/finetune/figment_sft_v7_delta_manifest.json`: v7 delta generation evidence. +- `data/finetune/figment_sft_v7.jsonl`: final merged corpus. +- `data/finetune/figment_sft_v7_case_specs.jsonl`: merged case specs. +- `data/finetune/figment_sft_v7_manifest.json`: final corpus manifest. +- `data/finetune/modal/figment_sft_v7/train.jsonl`: Modal training split. +- `data/finetune/modal/figment_sft_v7/validation.jsonl`: Modal validation split. +- `data/finetune/modal/figment_sft_v7/manifest.json`: Modal split manifest. + +Modify: + +- `scripts/generate_finetune_data.py`: add v7 failure classes, v7 scoring checks, and source-card closure policy. +- `scripts/augment_finetune_repair_rows.py`: add `source_card_closure` and `observation_patch_repair` repair scopes. +- `scripts/verify_finetune_harness_alignment.py`: add v7 closure verifier checks. +- `scripts/prepare_modal_finetune_dataset.py`: no behavioral change expected; use existing split command and verify group balance. + +## Implementation Tasks + +### Task 1: Summarize V6 Corpus Needs + +**Files:** + +- Create: `scripts/summarize_v7_corpus_needs.py` +- Read: `traces/figment_sft_v6_field_workflow_holdout_modal_gpu_20260611_h100_gguf/local_4b_eval.jsonl` +- Write: `traces/figment_sft_v6_field_workflow_holdout_modal_gpu_20260611_h100_gguf/v7_corpus_needs_summary.json` + +- [ ] Add a script that reads the v6 eval JSONL and writes: + - `total_cases` + - `competence_failure_case_ids` + - `expected_label_failure_case_ids` + - `expected_label_check_failures` + - `missing_source_card_ids_by_case` + - `deterministic_patch_fields_by_case` + - `deterministic_patch_field_counts` + - `actual_source_card_sets_for_failures` + +- [ ] Run: + +```bash +PYTHONPATH=. .venv/bin/python scripts/summarize_v7_corpus_needs.py \ + --eval-jsonl traces/figment_sft_v6_field_workflow_holdout_modal_gpu_20260611_h100_gguf/local_4b_eval.jsonl \ + --output traces/figment_sft_v6_field_workflow_holdout_modal_gpu_20260611_h100_gguf/v7_corpus_needs_summary.json +``` + +Expected: + +- `total_cases` is `150`. +- `competence_failure_case_ids` has `8` items. +- `expected_label_failure_case_ids` has `4` items. +- `missing_source_card_ids_by_case` includes `SAFETY-BOUNDARIES-v1` and `REFERRAL-SBAR-v1`. +- `deterministic_patch_field_counts.source_cards` is `6`. + +### Task 2: Add V7 Source-Card Closure Policy + +**Files:** + +- Modify: `scripts/generate_finetune_data.py` +- Modify: `scripts/verify_finetune_harness_alignment.py` +- Test: `tests/test_finetune_v7_data_plan.py` + +- [ ] Add a helper in `scripts/generate_finetune_data.py`: + +```python +def v7_source_card_closure_issues(output: dict, *, target_protocol_card_id: str | None = None) -> list[str]: + issues: list[str] = [] + source_cards = {str(card_id) for card_id in output.get("source_cards") or []} + if target_protocol_card_id and target_protocol_card_id not in source_cards: + issues.append(f"missing_target_source_card:{target_protocol_card_id}") + if output.get("handoff_note_sbar") and "REFERRAL-SBAR-v1" not in source_cards: + issues.append("missing_referral_sbar_source_card") + safety_text = json.dumps( + { + "safety_boundary": output.get("safety_boundary"), + "do_not_do": output.get("do_not_do"), + "responder_plain_language_script": output.get("responder_plain_language_script"), + }, + sort_keys=True, + ).lower() + safety_terms = ( + "local protocol", + "do not diagnose", + "do not provide clinical orders", + "do not provide treatment instructions", + "safety boundary", + ) + if any(term in safety_text for term in safety_terms) and "SAFETY-BOUNDARIES-v1" not in source_cards: + issues.append("missing_safety_boundaries_source_card") + return issues +``` + +- [ ] Wire the helper into the v7 candidate scorer so v7 rows are rejected on any closure issue. + +- [ ] Add verifier checks that report issue types: + - `v7_missing_referral_sbar_source_card` + - `v7_missing_safety_boundaries_source_card` + - `v7_missing_target_source_card` + +- [ ] Add tests that construct one row per failure type and assert the verifier rejects them. + +Run: + +```bash +PYTHONPATH=. .venv/bin/pytest tests/test_finetune_v7_data_plan.py tests/test_finetune_v6_data_plan.py -q +``` + +Expected: + +- v7 tests pass. +- v6 tests still pass. + +### Task 3: Build V7 Replay Selector + +**Files:** + +- Create: `scripts/build_v7_replay_corpus.py` +- Test: `tests/test_finetune_v7_data_plan.py` +- Write: `data/finetune/figment_sft_v7_replay.jsonl` +- Write: `data/finetune/figment_sft_v7_replay_manifest.json` + +- [ ] Start from `scripts/build_v6_replay_corpus.py`. + +- [ ] Set default inputs: + +```python +DEFAULT_INPUTS = [ + Path("data/finetune/figment_sft_v6_delta.jsonl"), + Path("data/finetune/figment_sft_v6_replay.jsonl"), + Path("data/finetune/figment_sft_v5.jsonl"), + Path("data/finetune/figment_sft_v4.jsonl"), + Path("data/finetune/figment_sft_v3.jsonl"), +] +``` + +- [ ] Set default targets: + +```python +DEFAULT_TARGETS = { + "figment_sft_v6_delta": 1430, + "figment_sft_v6_replay": 570, + "figment_sft_v5": 0, + "figment_sft_v4": 0, + "figment_sft_v3": 0, +} +``` + +- [ ] Apply v6 replay policy first, then apply v7 closure policy. + +- [ ] Annotate selected rows with: + +```json +{ + "v7_replay_audit": { + "source_dataset_version": "figment_sft_v6_delta", + "policy_version": 1, + "accepted": true + } +} +``` + +- [ ] Run: + +```bash +PYTHONPATH=. .venv/bin/python scripts/build_v7_replay_corpus.py +``` + +Expected: + +- `data/finetune/figment_sft_v7_replay.jsonl` has `2000` rows. +- Manifest `selected_by_source_bucket` includes `figment_sft_v6_delta: 1430` and `figment_sft_v6_replay: 570`. +- Manifest includes nonzero rejected counts for v7 closure issues if any candidate rows fail closure. + +### Task 4: Add V7 Generation Categories + +**Files:** + +- Modify: `scripts/generate_finetune_data.py` +- Modify: `scripts/augment_finetune_repair_rows.py` +- Test: `tests/test_finetune_v7_data_plan.py` + +- [ ] Add v7 navigator counts: + +```python +V7_NAVIGATOR_COUNTS = { + "source_card_closure": 240, + "observation_source_joint": 140, + "distractor_card_resistance": 100, + "sbar_source_coupling": 80, +} +``` + +- [ ] Add v7 repair counts: + +```python +V7_REPAIR_COUNTS = { + "source_card_closure": 160, + "source_card_negative_correction": 50, + "observation_patch_repair": 30, +} +``` + +- [ ] Add `_failure_class_for_index(..., dataset_version="figment_sft_v7_delta")` coverage so the first `20` rows interleave all v7 navigator categories. + +- [ ] Add repair scope scheduling so `figment_sft_v7_delta` produces: + +```python +{ + "source_card_closure": 160, + "source_card_negative_correction": 50, + "observation_patch_repair": 30, +} +``` + +- [ ] Add tests asserting the category counts exactly match the constants. + +Run: + +```bash +PYTHONPATH=. .venv/bin/pytest tests/test_finetune_v7_data_plan.py tests/test_finetune_v6_data_plan.py -q +``` + +Expected: + +- v7 category-count tests pass. +- v6 category-count tests still pass. + +### Task 5: Add V7 Full-Corpus Wrapper + +**Files:** + +- Create: `scripts/generate_v7_full_corpus.py` +- Test: `tests/test_finetune_v7_data_plan.py` + +- [ ] Create a wrapper patterned after `scripts/generate_v6_full_corpus.py`. + +- [ ] Pin defaults: + +```python +DEFAULT_OUTPUT_VERSION = "figment_sft_v7_delta" +DEFAULT_TEACHER_MODEL_ID = "nvidia/nemotron-3-ultra-550b-a55b:free" +DEFAULT_NAVIGATOR_COUNT = 560 +DEFAULT_REPAIR_COUNT = 240 +DEFAULT_BASE_START_INDEX = "80000" +DEFAULT_SHARD_PREFIX = "data/finetune/shards/figment_sft_v7_delta_full_shard" +``` + +- [ ] Ensure the default output paths are: + +```text +data/finetune/figment_sft_v7_delta.jsonl +data/finetune/figment_sft_v7_delta_case_specs.jsonl +data/finetune/figment_sft_v7_delta_manifest.json +data/finetune/modal/figment_sft_v7_delta +``` + +- [ ] Add a wrapper test that calls: + +```python +args = build_corpus_args(["--navigator-count", "5", "--repair-count", "3", "--dry-run"]) +``` + +and asserts: + +- dataset version is `figment_sft_v7_delta`; +- teacher model is `nvidia/nemotron-3-ultra-550b-a55b:free`; +- output path is `data/finetune/figment_sft_v7_delta.jsonl`; +- dry-run flag is preserved. + +Run: + +```bash +PYTHONPATH=. .venv/bin/pytest tests/test_finetune_v7_data_plan.py -q +``` + +Expected: + +- wrapper defaults are pinned by tests. + +### Task 6: Smoke Generate V7 Delta + +**Files:** + +- Write: `/tmp/figment_v7_smoke/figment_sft_v7_delta.jsonl` +- Write: `/tmp/figment_v7_smoke/figment_sft_v7_delta_case_specs.jsonl` +- Write: `/tmp/figment_v7_smoke/figment_sft_v7_delta_manifest.json` + +- [ ] Run a deterministic dry-run smoke: + +```bash +PYTHONPATH=. .venv/bin/python scripts/generate_v7_full_corpus.py \ + --navigator-count 8 \ + --repair-count 4 \ + --rows-per-shard 2 \ + --parallelism 1 \ + --base-start-index 88000 \ + --shard-prefix /tmp/figment_v7_smoke/shard \ + --output /tmp/figment_v7_smoke/figment_sft_v7_delta.jsonl \ + --case-specs /tmp/figment_v7_smoke/figment_sft_v7_delta_case_specs.jsonl \ + --manifest /tmp/figment_v7_smoke/figment_sft_v7_delta_manifest.json \ + --modal-output-dir /tmp/figment_v7_smoke/modal \ + --dry-run +``` + +Expected: + +- `12` total rows. +- At least one row from each v7 navigator category appears in the manifest or smoke distribution. +- Harness verifier reports `issue_count=0`. + +- [ ] Run a real-teacher smoke: + +```bash +PYTHONPATH=. .venv/bin/python scripts/generate_v7_full_corpus.py \ + --navigator-count 8 \ + --repair-count 4 \ + --rows-per-shard 2 \ + --parallelism 1 \ + --teacher-error-retries 3 \ + --teacher-error-sleep-seconds 10 \ + --base-start-index 88100 \ + --shard-prefix /tmp/figment_v7_teacher_smoke/shard \ + --output /tmp/figment_v7_teacher_smoke/figment_sft_v7_delta.jsonl \ + --case-specs /tmp/figment_v7_teacher_smoke/figment_sft_v7_delta_case_specs.jsonl \ + --manifest /tmp/figment_v7_teacher_smoke/figment_sft_v7_delta_manifest.json \ + --modal-output-dir /tmp/figment_v7_teacher_smoke/modal \ + --log-rejections +``` + +Expected: + +- `12` accepted rows. +- Verifier reports `issue_count=0`. +- Teacher rejection reasons, if any, are source-card closure, JSON parsing, or policy rejections recorded in the manifest. + +### Task 7: Generate Full V7 Delta + +**Files:** + +- Write: `data/finetune/figment_sft_v7_delta.jsonl` +- Write: `data/finetune/figment_sft_v7_delta_case_specs.jsonl` +- Write: `data/finetune/figment_sft_v7_delta_manifest.json` +- Write: `data/finetune/modal/figment_sft_v7_delta/train.jsonl` +- Write: `data/finetune/modal/figment_sft_v7_delta/validation.jsonl` +- Write: `data/finetune/modal/figment_sft_v7_delta/manifest.json` + +- [ ] Run: + +```bash +PYTHONPATH=. .venv/bin/python scripts/generate_v7_full_corpus.py \ + --parallelism 4 \ + --teacher-error-retries 3 \ + --teacher-error-sleep-seconds 10 \ + --log-rejections +``` + +Expected: + +- `data/finetune/figment_sft_v7_delta.jsonl` has `800` rows. +- `data/finetune/figment_sft_v7_delta_case_specs.jsonl` has case specs for all navigator rows. +- Manifest category counts match the v7 target. +- Harness verifier reports `issue_count=0`. + +### Task 8: Merge V7 Corpus + +**Files:** + +- Create: `scripts/merge_v7_training_corpus.py` +- Read: `data/finetune/figment_sft_v7_delta.jsonl` +- Read: `data/finetune/figment_sft_v7_replay.jsonl` +- Write: `data/finetune/figment_sft_v7.jsonl` +- Write: `data/finetune/figment_sft_v7_case_specs.jsonl` +- Write: `data/finetune/figment_sft_v7_manifest.json` +- Write: `data/finetune/modal/figment_sft_v7/train.jsonl` +- Write: `data/finetune/modal/figment_sft_v7/validation.jsonl` +- Write: `data/finetune/modal/figment_sft_v7/manifest.json` + +- [ ] Create merge logic patterned after `scripts/merge_v6_training_corpus.py`. + +- [ ] Set defaults: + +```python +DEFAULT_DELTA = Path("data/finetune/figment_sft_v7_delta.jsonl") +DEFAULT_DELTA_CASE_SPECS = Path("data/finetune/figment_sft_v7_delta_case_specs.jsonl") +DEFAULT_REPLAY = Path("data/finetune/figment_sft_v7_replay.jsonl") +DEFAULT_OUTPUT = Path("data/finetune/figment_sft_v7.jsonl") +DEFAULT_CASE_SPECS = Path("data/finetune/figment_sft_v7_case_specs.jsonl") +DEFAULT_MANIFEST = Path("data/finetune/figment_sft_v7_manifest.json") +DEFAULT_MODAL_DIR = Path("data/finetune/modal/figment_sft_v7") +``` + +- [ ] Run: + +```bash +PYTHONPATH=. .venv/bin/python scripts/merge_v7_training_corpus.py +``` + +Expected: + +- `data/finetune/figment_sft_v7.jsonl` has `2800` rows. +- Manifest records `delta_rows=800`. +- Manifest records `replay_rows=2000`. +- Harness verifier reports `issue_count=0`. +- Modal split has `2520` train rows and `280` validation rows. + +### Task 9: Final Verification + +**Files:** + +- Read: `data/finetune/figment_sft_v7.jsonl` +- Read: `data/finetune/figment_sft_v7_case_specs.jsonl` +- Read: `data/finetune/figment_sft_v7_manifest.json` +- Read: `data/finetune/modal/figment_sft_v7/manifest.json` + +- [ ] Count rows: + +```bash +wc -l data/finetune/figment_sft_v7.jsonl \ + data/finetune/figment_sft_v7_delta.jsonl \ + data/finetune/figment_sft_v7_replay.jsonl \ + data/finetune/modal/figment_sft_v7/train.jsonl \ + data/finetune/modal/figment_sft_v7/validation.jsonl +``` + +Expected: + +- `2800 data/finetune/figment_sft_v7.jsonl` +- `800 data/finetune/figment_sft_v7_delta.jsonl` +- `2000 data/finetune/figment_sft_v7_replay.jsonl` +- `2520 data/finetune/modal/figment_sft_v7/train.jsonl` +- `280 data/finetune/modal/figment_sft_v7/validation.jsonl` + +- [ ] Run verifier: + +```bash +PYTHONPATH=. .venv/bin/python scripts/verify_finetune_harness_alignment.py \ + --dataset data/finetune/figment_sft_v7.jsonl \ + --case-specs data/finetune/figment_sft_v7_case_specs.jsonl +``` + +Expected: + +- `passed` is `true`. +- `issue_count` is `0`. +- `rows` is `2800`. + +- [ ] Run tests: + +```bash +PYTHONPATH=. .venv/bin/pytest \ + tests/test_finetune_v7_data_plan.py \ + tests/test_finetune_v6_data_plan.py \ + tests/test_v6_replay_selection.py \ + tests/test_modal_finetune_prep.py \ + -q +``` + +Expected: + +- all tests pass. + +## Training Readiness Gates + +Do not launch v7 training until all gates pass: + +- `data/finetune/figment_sft_v7.jsonl` exists and has `2800` rows. +- `data/finetune/figment_sft_v7_manifest.json` exists. +- `data/finetune/modal/figment_sft_v7/train.jsonl` has `2520` rows. +- `data/finetune/modal/figment_sft_v7/validation.jsonl` has `280` rows. +- Harness alignment verifier reports `issue_count=0`. +- V7 tests pass. +- The manifest shows nonzero counts for: + - `source_card_closure` + - `focused_repair:source_card_closure` + - `observation_source_joint` + - `distractor_card_resistance` + - `sbar_source_coupling` +- The manifest shows the corpus includes all `570` v6 replay rows and all `1430` v6 delta rows. +- No holdout eval case IDs appear as training `case_id` values. + +## Post-Training Acceptance Gates + +Run v7 against `data/eval/field_workflow_holdout_v1.jsonl` on Modal GPU using the same harness/scoring path as v5 and v6. + +V7 should beat v6 if: + +- `final_validation_successes == 150` +- `fallback_uses == 0` +- `expected_label_successes == 150` +- `expected_label_check_failures.expected_source_cards_present == 0` +- `competence_successes >= 146` +- `deterministic_patch_count <= 15` +- `field_provenance_by_field.source_cards.deterministic_fallback <= 1` +- `field_provenance_by_field.missing_info_to_collect.deterministic_fallback <= 5` +- `field_provenance_by_field.next_observations_to_collect.deterministic_fallback <= 5` +- `handoff_unsupported_fact_total == 0` + +V7 should be rejected or rolled into a v8 data plan if: + +- expected-label success stays below `150/150`; +- source-card deterministic fallback remains above `1/150`; +- observation deterministic fallback rises above v6's `7/150` for either observation field; +- final validation fails on any case; +- fallback uses become nonzero; +- source-card closure improves only by over-citing irrelevant retrieved cards. + +## Notes For Training + +Recommended training posture: + +- Start from the v6 adapter, not from base, because v6 already internalized most of the harness behavior. +- Use H100 for the full run because the user has already chosen faster Modal iteration. +- Keep the learning rate conservative relative to v6 if the trainer supports it, because v7 is a targeted continuation rather than a broad skill rebuild. +- After training, upload the merged BF16 artifact to the existing Hugging Face archive path for v7. +- Evaluate on Modal as a detached batch job that exits after writing artifacts. + +Suggested output names: + +- Dataset version: `figment_sft_v7` +- Adapter output name: `figment-sft-v7-lora` +- Merged output name: `figment-sft-v7-lora-merged-bf16` +- Modal checkpoint path: `figment-checkpoints:/figment_sft_v7/figment-sft-v7-lora` +- Modal merged path: `figment-checkpoints:/figment_sft_v7/figment-sft-v7-lora-merged-bf16` +- Eval result name: `figment_sft_v7_field_workflow_holdout_modal_gpu_20260611_h100_gguf` + +## Self-Review Checklist + +- [ ] The plan reuses v6 heavily instead of regenerating the entire corpus. +- [ ] The plan does not directly train on holdout eval examples. +- [ ] The new data categories target the actual v6 failures. +- [ ] The replay policy blocks v5-style scaffold dependence. +- [ ] The corpus shape preserves observation ownership instead of over-rotating on source cards. +- [ ] The final gates can prove whether v7 improved over v6. diff --git a/docs/local_parakeet_asr_evidence.md b/docs/local_parakeet_asr_evidence.md new file mode 100644 index 0000000000000000000000000000000000000000..99adb6ef3692833a4610aec7f2714911d21094d5 --- /dev/null +++ b/docs/local_parakeet_asr_evidence.md @@ -0,0 +1,56 @@ +# Local Parakeet ASR evidence + +Date: 2026-06-07 + +This note separates local Parakeet ASR artifact availability from a real local ASR proof. Artifact availability is not proof that the app has used Parakeet audio or that the local/off-grid audio path is ready. + +## Artifact status + +- Model repo: `nvidia/parakeet-rnnt-1.1b` +- Revision: `a07b19e98a26c1873a3f2622c446a4a1ca6316cb` +- Local snapshot path: `/Users/drake.thomsen/.cache/huggingface/hub/models--nvidia--parakeet-rnnt-1.1b/snapshots/a07b19e98a26c1873a3f2622c446a4a1ca6316cb` +- Local artifact: `parakeet-rnnt-1.1b.nemo` +- Artifact size: `4283105280` bytes +- Artifact SHA-256: `535896f014953d945b287ac533560e20da8103c6781b152de4645528e2b60738` + +## Evidence helper + +Use the helper to capture local ASR evidence: + +```bash +PYTHON_DOTENV_DISABLED=true \ +python3 scripts/run_local_asr_evidence.py \ + --provider-payload \ + --audio \ + --provider-note "" +``` + +The helper writes a timestamped evidence directory under `traces/local_asr_parakeet_evidence_*`: + +- `artifact_metadata.json`: Parakeet `.nemo` presence, size, and hash +- `audio_metadata.json`: optional source-audio metadata and hash only; raw audio is not copied into the evidence bundle +- `provider_payload_metadata.json`: provider output file hash +- `audio_draft.json`: Figment draft generated from the provider payload under `AUDIO_BACKEND=parakeet_nemo` and `ALLOW_LOCAL_ASR=true` +- `draft_checks.json`: evidence-gated checks for Parakeet provenance, confirmation status, and raw-audio handling +- `asr_evidence_manifest.json`: compact manifest with artifact status, provider-payload hash, configured route, draft summary, raw-audio handling, and proof flags +- `summary.json`: top-level proof flags + +Exit codes are evidence-gated: + +- `0`: provider payload passed all local ASR draft checks +- `2`: artifact exists but provider payload is missing or not proof +- `1`: artifact missing + +## Current result + +The artifact-only helper run succeeded in finding the Parakeet `.nemo` file but exited `2` because no real local ASR provider payload was supplied: + +```text +status=artifact_present_provider_payload_required +counts_as_local_asr_artifact=true +counts_as_local_asr_proof=false +raw_audio_stored=false +asr_evidence_manifest_path=/tmp/figment-local-asr-artifact-only-manifest-check/asr_evidence_manifest.json +``` + +This means Parakeet remains not demo-visible as local ASR proof. It can become proof only after a real local ASR adapter or device runtime produces a provider payload, and the helper records `counts_as_local_asr_proof=true`. diff --git a/docs/superpowers/plans/2026-06-10-figment-build-small-blog.md b/docs/superpowers/plans/2026-06-10-figment-build-small-blog.md new file mode 100644 index 0000000000000000000000000000000000000000..e82593e1ee9d2faeab7136b4318b7940d5ec0497 --- /dev/null +++ b/docs/superpowers/plans/2026-06-10-figment-build-small-blog.md @@ -0,0 +1,90 @@ +# Figment Build Small Blog Implementation Plan + +> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking. + +**Goal:** Create a rough judge-facing Build Small blog post about what Figment taught me. + +**Architecture:** The deliverable is a single markdown draft under `docs/`, based on the approved design spec. It should use evidence from project docs, prior thread summaries, git history, Modal metadata, and eval traces while keeping the tone public and readable. + +**Tech Stack:** Markdown documentation in the existing Figment repo. + +--- + +### Task 1: Draft The Blog Post + +**Files:** +- Create: `docs/figment-build-small-lessons-draft.md` +- Reference: `docs/superpowers/specs/2026-06-10-figment-build-small-blog-design.md` + +- [x] **Step 1: Create the draft markdown file** + +Write a rough post with these sections: + +```markdown +# Building Figment For Build Small: What I Learned About Making Small Models Useful + +Opening: Figment is a protocol navigator for field responders, not an AI doctor or autonomous clinical decision tool. + +## Audio Should Draft, Not Decide + +## Deterministic Safety Rules Are The Floor + +## App Safety And Model Competence Are Different Numbers + +## Field-Level Provenance Changed My Relationship With Fallback + +## Fine-Tuning Only Helped After The Eval Got More Honest + +## What Still Is Not Good Enough + +## What I Would Build Next + +## The Lesson I Am Taking From Build Small +``` + +- [x] **Step 2: Include evidence anchors** + +Use these exact evidence points where they naturally fit: + +- Hosted Omni baseline: `28/50` model competence, `50/50` final validation. +- Hosted load-bearing follow-up: `31/50` whole-output competence, `480/650` model-retained fields. +- Local v1 pilot: proved the train/merge/convert/serve/eval loop but regressed to `11/50`. +- Local v2: `33/50` on the locked 50-case eval. +- Local v3 holdout: `107/150` competence, `148/150` final validation. +- V3 weakness: `REFERRAL-SBAR-v1` `0/27`, `radio_handoff` `0/16`, `sbar_handoff_usefulness` `0/10`. +- Modal v3: `700/700` steps, final `eval_loss=0.04357146`, final `train_loss=0.60960097`. + +- [x] **Step 3: Avoid unsafe or unsupported claims** + +Check the draft does not claim: + +- clinical validation, +- diagnosis or treatment, +- autonomous triage, +- complete local/off-grid proof, +- final validation as pure model competence, +- v3 as solved handoff usefulness. + +- [x] **Step 4: Self-edit for public readability** + +Read the full draft once and tighten: + +- make section openings concrete, +- remove repeated metrics, +- keep caveats readable, +- preserve the "systems of restraint" closing. + +- [x] **Step 5: Verify and commit** + +Run: + +```bash +rg -n "diagnose|prescribe|clinical validation|autonomous triage|off-grid proof|TODO|TBD" docs/figment-build-small-lessons-draft.md +git diff --check +``` + +Expected: + +- Any medical-risk phrases appear only as disclaimers or non-goals. +- No placeholder text. +- `git diff --check` prints no output. diff --git a/docs/superpowers/specs/2026-06-10-figment-build-small-blog-design.md b/docs/superpowers/specs/2026-06-10-figment-build-small-blog-design.md new file mode 100644 index 0000000000000000000000000000000000000000..7df1d29c5acf218a323245a5a95ca7cdf198469e --- /dev/null +++ b/docs/superpowers/specs/2026-06-10-figment-build-small-blog-design.md @@ -0,0 +1,83 @@ +# Figment Build Small Blog Post Design + +Date: 2026-06-10 + +## Purpose + +Write a rough blog post about what I learned while building Figment for the Hugging Face Build Small Hackathon. + +The post should primarily serve judges and public project readers, while still being useful to other builders. It should be candid about failed evals, fallback, training iteration, and remaining weaknesses, but should not read like an internal debugging diary. + +## Audience + +Primary: + +- Hugging Face Build Small judges. +- Public readers who want to understand what Figment proves and what it does not yet prove. + +Secondary: + +- Hackathon builders and AI engineers interested in small-model product design. + +## Tone + +Use earned candor: + +- Be honest about the messy parts. +- Separate app safety from model competence. +- Keep the center of gravity on what was learned and why the project improved. +- Avoid overclaiming medical, local/off-grid, or fine-tuning success. + +The voice should sound like a reflective builder: technical, grounded, and specific, but still readable as a public blog post. + +## Recommended Angle + +Use a hybrid of: + +1. The field tool story. + - Figment is a protocol navigator for rural clinics, mobile units, and disaster response contexts. + - It is not an AI doctor. + +2. The small models need systems story. + - Small models become useful when surrounded by scope, contracts, validators, provenance, traces, and honest evals. + +Use the evaluation/training evidence as proof points throughout rather than opening with a wall of metrics. + +## Proposed Structure + +1. Set the scene: why Figment exists and why the Build Small constraint mattered. +2. Lesson 1: audio should draft, not decide. +3. Lesson 2: deterministic safety rules are not a fallback; they are the floor. +4. Lesson 3: model competence and app safety are different numbers. +5. Lesson 4: field-level provenance changed how fallback felt. +6. Lesson 5: fine-tuning worked only after the eval measured the real workflow. +7. What still is not good enough: SBAR and radio handoff usefulness. +8. What comes next: focused v4 work on handoff, cue ownership, and workflow metrics. +9. Closing: Build Small taught me that useful small-model apps are systems of restraint. + +## Evidence To Include + +Use these numbers sparingly, as anchors: + +- Hosted Omni baseline eval: `28/50` hosted model competence and `50/50` final validation. +- Hosted Omni load-bearing follow-up: `31/50` whole-output competence, `8/50` full fallback, `480/650` model-retained fields, `170/650` deterministic patches. +- Local 4B baseline after scaffolding: `26/50` competence, mostly via repair, with `50/50` final validation. +- Local 4B v1 pilot: proved the train, merge, convert, serve, and eval loop, but regressed competence to `11/50`. +- Local 4B v2: improved to `33/50` on the locked 50-case eval. +- Local 4B v3 field-workflow holdout: `107/150` competence, `93/150` raw successes, `14/150` repairs, `2/150` full fallbacks, `148/150` final validation. +- V3 weakness: `REFERRAL-SBAR-v1` at `0/27`, `radio_handoff` at `0/16`, `sbar_handoff_usefulness` at `0/10`. +- Modal v3 training: `700/700` steps, final `eval_loss=0.04357146`, final `train_loss=0.60960097`, artifacts present in `figment-checkpoints:/figment_sft_v3/figment-sft-v3-lora`. + +## Claims To Avoid + +- Do not claim Figment is clinically validated. +- Do not claim it diagnoses, prescribes, or makes autonomous triage decisions. +- Do not claim final validation is pure model competence. +- Do not claim local/off-grid proof is complete unless referring narrowly to recorded local text-model evidence. +- Do not imply the v3 fine-tune solved handoff usefulness. + +## Drafting Notes + +The rough draft should read as a blog post, not a project README. It can use section headings, short paragraphs, and a few concrete metrics. It should emphasize decisions and lessons, not implementation minutiae. + +The strongest closing thought is that "small" was not just about model size. It was about narrowing the job until the model could be useful, measured, and corrected. diff --git a/figment/harness_evidence.py b/figment/harness_evidence.py new file mode 100644 index 0000000000000000000000000000000000000000..62bbe3ebf9e446ded8a06258ddc53561968f4ba8 --- /dev/null +++ b/figment/harness_evidence.py @@ -0,0 +1,94 @@ +"""Deterministic evidence surfaces for Figment navigator outputs and traces.""" + +from __future__ import annotations + +from collections.abc import Iterable, Mapping +from typing import Any + + +def build_harness_evidence( + *, + confirmed_intake: Mapping[str, Any] | None, + retrieved_card_ids: Iterable[Any], + rule_results: Iterable[Mapping[str, Any]], + urgency_floor: str, + validator_result: Mapping[str, Any], + final_output: Mapping[str, Any] | None = None, + model_route: Mapping[str, Any] | None = None, + audio: Mapping[str, Any] | None = None, +) -> dict[str, Any]: + """Build app-owned, non-secret evidence badges for a navigator result.""" + + route = model_route or {} + output = final_output or {} + validation_status = _validation_status(validator_result) + return { + "confirmed_intake": bool(confirmed_intake and confirmed_intake.get("confirmed") is True), + "retrieved_card_ids": _unique_strings(retrieved_card_ids), + "deterministic_rule_ids": _unique_strings(rule.get("rule_id") for rule in rule_results), + "deterministic_rule_card_ids": _unique_strings(rule.get("card_id") for rule in rule_results), + "urgency_floor": str(urgency_floor), + "validator_status": validation_status, + "audio_correction_status": _audio_correction_status(audio), + "source_card_ids": _unique_strings(output.get("source_cards", [])), + "fallback_tier": _optional_string(route.get("fallback_tier")), + "fallback_reason": _optional_string(route.get("fallback_reason")), + "final_route": _optional_string(route.get("final_route") or route.get("runtime_contribution")) + or "unknown", + "field_level_fallback_used": bool(route.get("field_level_fallback_used")), + "repair_attempt_count": _int_or_zero(route.get("repair_attempt_count")), + "repair_scopes": _unique_strings(route.get("repair_scopes", [])), + } + + +def _validation_status(validator_result: Mapping[str, Any]) -> str: + if validator_result.get("passed") is True: + return "passed" + if validator_result.get("passed") is False: + return "failed" + return "unknown" + + +def _audio_correction_status(audio: Mapping[str, Any] | None) -> str: + if not isinstance(audio, Mapping) or not audio: + return "not_applicable" + correction_keys = ( + "manual_corrections", + "manual_correction", + "corrected_fields", + "corrections_applied", + "human_corrected_fields", + ) + if any(audio.get(key) for key in correction_keys): + return "corrected" + if audio.get("transcript") or audio.get("fields") or audio.get("structured_intake_patch"): + return "no_manual_correction_recorded" + return "not_applicable" + + +def _unique_strings(values: Iterable[Any]) -> list[str]: + out: list[str] = [] + for value in values: + if value is None: + continue + text = str(value).strip() + if text and text not in out: + out.append(text) + return out + + +def _optional_string(value: Any) -> str | None: + if value is None: + return None + text = str(value).strip() + return text or None + + +def _int_or_zero(value: Any) -> int: + try: + return int(value) + except (TypeError, ValueError): + return 0 + + +__all__ = ["build_harness_evidence"] diff --git a/figment/observation_targets.py b/figment/observation_targets.py new file mode 100644 index 0000000000000000000000000000000000000000..b62660a66ee1e286a1fbb86251d2067daa971c2c --- /dev/null +++ b/figment/observation_targets.py @@ -0,0 +1,521 @@ +"""Deterministic scaffolding helpers for required observation targets.""" + +from __future__ import annotations + +from collections.abc import Iterable, Mapping +from copy import deepcopy +from dataclasses import dataclass, field +import re +from typing import Any + + +CARD_IDS_EXEMPT_FROM_OBSERVATION_TARGETS = {"SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"} +TRACE_ONLY_REQUIRED_OBSERVATION_IDS_KEY = "selected_required_observation_ids" +URGENCY_ORDER = {"routine": 0, "monitor": 1, "urgent": 2, "emergency": 3} +TARGET_TOKEN_STOPWORDS = { + "a", + "an", + "and", + "or", + "the", + "to", + "of", + "for", + "if", + "by", + "with", +} + + +@dataclass(frozen=True) +class NavigationScaffoldResult: + """Navigator output after deterministic scaffolding plus changed fields.""" + + output: dict[str, Any] + patched_fields: set[str] + filled_required_observation_ids: list[str] + model_selected_required_observation_ids: list[str] = field(default_factory=list) + invalid_selected_required_observation_ids: list[str] = field(default_factory=list) + stripped_trace_only_fields: list[str] = field(default_factory=list) + + +def required_observation_targets(retrieved_cards: Iterable[Mapping[str, Any]]) -> list[dict[str, Any]]: + """Return stable target ids for required observations on retrieved cards.""" + + targets: list[dict[str, Any]] = [] + for item in retrieved_cards: + card = _card_payload(item) + card_id = str(card.get("card_id", "")).strip() + if not card_id: + continue + required_observations = card.get("required_observations") + if not isinstance(required_observations, list): + continue + title = str(card.get("title", "")).strip() + for index, observation in enumerate(required_observations, start=1): + display_text = str(observation).strip() + if not display_text: + continue + targets.append( + { + "id": f"{card_id}::required_observation::{index}", + "card_id": card_id, + "title": title, + "display_text": display_text, + "cue_tokens": _target_tokens(display_text), + } + ) + return targets + + +def build_case_fact_ledger(intake: Mapping[str, Any]) -> dict[str, list[dict[str, Any]]]: + """Split confirmed intake into present, absent/denied, and unclear facts.""" + + ledger = {"present": [], "absent_or_denied": [], "unclear": []} + if intake.get("confirmed") is not True: + ledger["unclear"].append( + { + "field": "confirmed", + "value": "intake is not confirmed", + } + ) + return ledger + + for field, value in sorted(intake.items()): + if field == "confirmed" or value is None: + continue + text = str(value).strip() + if not text: + continue + lowered = text.lower() + if lowered in {"unknown", "pending", "not recorded", "not available", "unclear"}: + ledger["unclear"].append({"field": field, "value": text}) + continue + ledger["present"].append({"field": field, "value": text}) + for phrase in _negated_phrases(text): + ledger["absent_or_denied"].append({"field": field, "value": phrase}) + return ledger + + +def apply_navigation_scaffolding( + output: Mapping[str, Any], + *, + retrieved_cards: Iterable[Mapping[str, Any]], + rule_results: list[dict[str, Any]], + urgency_floor: str, + confirmed_intake: Mapping[str, Any] | None = None, +) -> NavigationScaffoldResult: + """Patch deterministic control fields and required-observation omissions.""" + + patched = deepcopy(dict(output)) + patched_fields: set[str] = set() + retrieved_card_list = list(retrieved_cards) + retrieved_ids = _retrieved_card_ids(retrieved_card_list) + fired_card_ids = _fired_rule_card_ids(rule_results) + targets = required_observation_targets(retrieved_card_list) + ( + model_selected_required_observation_ids, + invalid_selected_required_observation_ids, + stripped_trace_only_fields, + ) = _pop_trace_only_required_observation_ids(patched, targets) + + current_urgency = str(patched.get("protocol_urgency", "")).strip() + if not _urgency_at_least(current_urgency, urgency_floor): + patched["protocol_urgency"] = urgency_floor + patched_fields.add("protocol_urgency") + + expected_red_flags = list(rule_results) + if patched.get("red_flags") != expected_red_flags: + patched["red_flags"] = expected_red_flags + patched_fields.add("red_flags") + + source_cards = _scaffold_source_cards(patched.get("source_cards"), retrieved_ids, fired_card_ids) + if patched.get("source_cards") != source_cards: + patched["source_cards"] = source_cards + patched_fields.add("source_cards") + + pathways = _scaffold_candidate_pathways( + patched.get("candidate_protocol_pathways"), + source_cards, + fired_card_ids, + ) + if patched.get("candidate_protocol_pathways") != pathways: + patched["candidate_protocol_pathways"] = pathways + patched_fields.add("candidate_protocol_pathways") + + filled_ids = _fill_required_observation_targets( + patched, + targets, + selected_required_observation_ids=model_selected_required_observation_ids, + ) + if filled_ids: + patched_fields.update({"missing_info_to_collect", "next_observations_to_collect"}) + + if confirmed_intake is not None and _scaffold_handoff_note_sbar( + patched, + confirmed_intake=confirmed_intake, + rule_results=rule_results, + urgency_floor=urgency_floor, + source_card_ids=source_cards, + ): + patched_fields.add("handoff_note_sbar") + + return NavigationScaffoldResult( + output=patched, + patched_fields=patched_fields, + filled_required_observation_ids=filled_ids, + model_selected_required_observation_ids=model_selected_required_observation_ids, + invalid_selected_required_observation_ids=invalid_selected_required_observation_ids, + stripped_trace_only_fields=stripped_trace_only_fields, + ) + + +def build_handoff_note_sbar_template( + intake: Mapping[str, Any], + rule_results: list[dict[str, Any]], + urgency_floor: str, + *, + source_card_ids: Iterable[Any] = (), +) -> dict[str, str]: + """Build a deterministic, grounded SBAR draft from confirmed harness facts.""" + + situation = _first_text( + intake.get("chief_concern"), + intake.get("responder_note"), + "Confirmed field concern", + ) + background_parts = [] + if _has_value(intake.get("setting")): + background_parts.append(f"Setting: {intake['setting']}.") + if _has_value(intake.get("patient_age")): + background_parts.append(f"Age: {intake['patient_age']}.") + if _has_value(intake.get("pregnancy_status")): + background_parts.append(f"Pregnancy status: {intake['pregnancy_status']}.") + + assessment_parts = [] + if _has_value(intake.get("symptoms")): + assessment_parts.append(f"Symptoms: {intake['symptoms']}.") + if _has_value(intake.get("vitals")): + assessment_parts.append(f"Vitals: {intake['vitals']}.") + red_flag_labels = [ + str(rule.get("label") or rule.get("rule_id")) + for rule in rule_results + if rule.get("label") or rule.get("rule_id") + ] + if red_flag_labels: + assessment_parts.append(f"Red flags: {'; '.join(red_flag_labels)}.") + + source_suffix = _source_card_suffix(source_card_ids) + return { + "situation": str(situation), + "background": " ".join(background_parts) or "Background details pending from confirmed intake.", + "assessment_observations_only": " ".join(assessment_parts) + or "Assessment observations pending from confirmed intake.", + "handoff_request": f"Request {urgency_floor} review/escalation per cited local protocol cards{source_suffix}.", + } + + +def targets_for_failure_cards( + targets: Iterable[Mapping[str, Any]], + failures: Iterable[str], +) -> list[dict[str, Any]]: + """Filter required-observation targets to card ids named in validation failures.""" + + failure_text = "\n".join(str(failure) for failure in failures) + card_ids = set(re.findall(r"\b[A-Z][A-Z0-9-]+-v\d+\b", failure_text)) + selected = [] + for target in targets: + card_id = str(target.get("card_id", "")).strip() + if card_id and (not card_ids or card_id in card_ids): + selected.append(dict(target)) + return selected + + +def _scaffold_handoff_note_sbar( + output: dict[str, Any], + *, + confirmed_intake: Mapping[str, Any], + rule_results: list[dict[str, Any]], + urgency_floor: str, + source_card_ids: Iterable[Any], +) -> bool: + template = build_handoff_note_sbar_template( + confirmed_intake, + rule_results, + urgency_floor, + source_card_ids=source_card_ids, + ) + handoff = output.get("handoff_note_sbar") + if not isinstance(handoff, Mapping): + output["handoff_note_sbar"] = template + return True + + patched_handoff = dict(handoff) + changed = False + for field, template_value in template.items(): + value = str(patched_handoff.get(field) or "").strip() + if not value or _handoff_slot_needs_scaffold(field, value, rule_results): + patched_handoff[field] = template_value + changed = True + if changed: + output["handoff_note_sbar"] = patched_handoff + return changed + + +def _handoff_slot_needs_scaffold(field: str, value: str, rule_results: list[dict[str, Any]]) -> bool: + normalized = _normalize_text(value) + if field == "assessment_observations_only" and _unsafe_assessment_language(normalized): + return True + if field == "assessment_observations_only" and rule_results: + rule_markers = [ + _normalize_text(str(rule.get(key, ""))) + for rule in rule_results + for key in ("rule_id", "label") + if rule.get(key) + ] + return "red flag" not in normalized and "rule" not in normalized and not any( + marker and marker in normalized for marker in rule_markers + ) + return False + + +def _unsafe_assessment_language(normalized_text: str) -> bool: + return bool( + re.search( + r"\b(?:diagnos(?:e|is|ed)|prescrib(?:e|ed|ing)|administer|discharge|treat(?:ment)?|dose|dosing)\b", + normalized_text, + ) + ) + + +def _fill_required_observation_targets( + output: dict[str, Any], + targets: list[dict[str, Any]], + *, + selected_required_observation_ids: Iterable[str] = (), +) -> list[str]: + source_cards = {str(card_id) for card_id in output.get("source_cards", []) if str(card_id)} + candidate_cards = { + str(pathway.get("card_id", "")).strip() + for pathway in output.get("candidate_protocol_pathways", []) + if isinstance(pathway, Mapping) and str(pathway.get("card_id", "")).strip() in source_cards + } + observation_cards = candidate_cards or source_cards + actionable_targets = [ + target + for target in targets + if target["card_id"] in observation_cards + and target["card_id"] not in CARD_IDS_EXEMPT_FROM_OBSERVATION_TARGETS + ] + if not actionable_targets: + return [] + + missing_info = _string_list(output.get("missing_info_to_collect")) + next_observations = _string_list(output.get("next_observations_to_collect")) + combined_text = "\n".join(missing_info + next_observations) + combined_tokens = set(_target_tokens(combined_text)) + + missing_targets = [ + target + for target in actionable_targets + if not _target_present(target, combined_text, combined_tokens) + ] + if not missing_targets: + return [] + + for target in missing_targets: + display_text = str(target["display_text"]) + missing_info.append(display_text) + next_observations.append(display_text) + output["missing_info_to_collect"] = missing_info + output["next_observations_to_collect"] = next_observations + return [str(target["id"]) for target in missing_targets] + + +def _target_present(target: Mapping[str, Any], text: str, tokens: set[str]) -> bool: + target_tokens = set(str(token) for token in target.get("cue_tokens", [])) + if target_tokens and target_tokens <= tokens: + return True + normalized_target = _normalize_text(str(target.get("display_text", ""))) + return bool(normalized_target and normalized_target in _normalize_text(text)) + + +def _pop_trace_only_required_observation_ids( + output: dict[str, Any], + targets: Iterable[Mapping[str, Any]], +) -> tuple[list[str], list[str], list[str]]: + if TRACE_ONLY_REQUIRED_OBSERVATION_IDS_KEY not in output: + return [], [], [] + + raw_value = output.pop(TRACE_ONLY_REQUIRED_OBSERVATION_IDS_KEY) + target_ids = {str(target.get("id", "")).strip() for target in targets} + target_ids.discard("") + selected: list[str] = [] + invalid: list[str] = [] + for target_id in _string_list(raw_value): + normalized = str(target_id).strip() + if not normalized: + continue + if normalized in target_ids: + _append_unique(selected, normalized) + else: + _append_unique(invalid, normalized) + return selected, invalid, [TRACE_ONLY_REQUIRED_OBSERVATION_IDS_KEY] + + +def _target_tokens(value: Any) -> list[str]: + tokens = re.findall(r"[a-z0-9]+", str(value).lower()) + return [token for token in tokens if token and token not in TARGET_TOKEN_STOPWORDS] + + +def _normalize_text(value: str) -> str: + return " ".join(re.findall(r"[a-z0-9]+", value.lower())) + + +def _card_payload(item: Mapping[str, Any]) -> Mapping[str, Any]: + card = item.get("card", item) + return card if isinstance(card, Mapping) else {} + + +def _retrieved_card_ids(retrieved_cards: Iterable[Mapping[str, Any]]) -> list[str]: + ids: list[str] = [] + for item in retrieved_cards: + card = _card_payload(item) + card_id = str(item.get("card_id") or card.get("card_id") or "").strip() + if card_id and card_id not in ids: + ids.append(card_id) + return ids + + +def _fired_rule_card_ids(rule_results: Iterable[Mapping[str, Any]]) -> list[str]: + ids: list[str] = [] + for rule in rule_results: + card_id = str(rule.get("card_id", "")).strip() + if card_id and card_id not in ids: + ids.append(card_id) + return ids + + +def _scaffold_source_cards(value: Any, retrieved_ids: list[str], fired_card_ids: list[str]) -> list[str]: + raw_source_cards = [str(card_id) for card_id in value if str(card_id)] if isinstance(value, list) else [] + allowed = set(retrieved_ids) | set(fired_card_ids) + source_cards: list[str] = [] + for card_id in fired_card_ids: + if card_id not in source_cards: + source_cards.append(card_id) + for card_id in raw_source_cards: + if card_id in allowed and card_id not in source_cards: + source_cards.append(card_id) + if not source_cards: + source_cards.extend(retrieved_ids[:3]) + return source_cards[:6] + + +def _scaffold_candidate_pathways( + value: Any, + source_cards: list[str], + fired_card_ids: list[str], +) -> list[dict[str, str]]: + source_set = set(source_cards) + pathways: list[dict[str, str]] = [] + if isinstance(value, list): + for item in value: + if not isinstance(item, Mapping): + continue + card_id = str(item.get("card_id", "")).strip() + if card_id not in source_set: + continue + pathways.append( + { + "card_id": card_id, + "reason_relevant": str(item.get("reason_relevant") or "Retrieved from confirmed intake."), + } + ) + pathway_ids = {pathway["card_id"] for pathway in pathways} + for card_id in fired_card_ids: + if card_id not in source_set: + continue + if card_id in pathway_ids: + continue + pathways.append( + { + "card_id": card_id, + "reason_relevant": "Required by deterministic rule or cited protocol context.", + } + ) + pathway_ids.add(card_id) + if not pathways: + fallback_source_cards = [ + card_id for card_id in source_cards if card_id not in CARD_IDS_EXEMPT_FROM_OBSERVATION_TARGETS + ] or source_cards + pathways = [ + { + "card_id": card_id, + "reason_relevant": "Retrieved from confirmed intake and deterministic protocol context.", + } + for card_id in fallback_source_cards[:3] + ] + return pathways + + +def _urgency_at_least(actual: str, expected_minimum: str) -> bool: + if actual not in URGENCY_ORDER or expected_minimum not in URGENCY_ORDER: + return False + return URGENCY_ORDER[actual] >= URGENCY_ORDER[expected_minimum] + + +def _string_list(value: Any) -> list[str]: + if isinstance(value, list): + return [str(item) for item in value if str(item)] + if isinstance(value, str) and value.strip(): + return [value.strip()] + return [] + + +def _append_unique(items: list[str], value: str) -> None: + if value not in items: + items.append(value) + + +def _negated_phrases(text: str) -> list[str]: + phrases: list[str] = [] + for match in re.finditer(r"\b(no|denies|denied|without)\s+([^,.;]+)", text, re.IGNORECASE): + marker = match.group(1).lower() + phrase = " ".join(match.group(2).split()).strip() + if not phrase: + continue + phrases.append(f"{marker} {phrase}") + return phrases + + +def _source_card_suffix(source_card_ids: Iterable[Any]) -> str: + ids = [str(card_id).strip() for card_id in source_card_ids if str(card_id).strip()] + return f" ({', '.join(ids[:4])})" if ids else "" + + +def _first_text(*values: Any) -> str: + for value in values: + if _has_value(value): + return str(value).strip() + return "" + + +def _has_value(value: Any) -> bool: + if value is None: + return False + if isinstance(value, str): + return bool(value.strip()) + if isinstance(value, (list, tuple, set, dict)): + return bool(value) + return True + + +__all__ = [ + "NavigationScaffoldResult", + "TRACE_ONLY_REQUIRED_OBSERVATION_IDS_KEY", + "apply_navigation_scaffolding", + "build_case_fact_ledger", + "build_handoff_note_sbar_template", + "required_observation_targets", + "targets_for_failure_cards", +] diff --git a/modal/eval_figment_nemotron.py b/modal/eval_figment_nemotron.py new file mode 100644 index 0000000000000000000000000000000000000000..9741f1082f5b16722c21d3ace365260376dd78c1 --- /dev/null +++ b/modal/eval_figment_nemotron.py @@ -0,0 +1,635 @@ +"""Modal batch eval for Figment's merged Nemotron 4B checkpoint. + +Run the full 150-case v5 eval as a terminating Modal job: + + .venv/bin/modal run modal/eval_figment_nemotron.py +""" + +from __future__ import annotations + +from datetime import UTC +from datetime import datetime +import json +from pathlib import Path +from typing import Any + +import modal + + +APP_NAME = "figment-nemotron-4b-batch-eval" +DEFAULT_DATASET_VERSION = "figment_sft_v5" +DEFAULT_MERGED_MODEL_NAME = "figment-sft-v5-lora-merged-bf16" +DEFAULT_MODEL_ID = "nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16" +DEFAULT_CASE_PATH = "data/eval/field_workflow_holdout_v1.jsonl" +DEFAULT_CASE_COUNT = 150 +DEFAULT_EVAL_GPU = "H100" +DEFAULT_CUDA_ARCHITECTURES = "90" +CHECKPOINT_VOLUME_NAME = "figment-checkpoints" +RESULT_VOLUME_NAME = "figment-eval-results" +CHECKPOINT_DIR = "/checkpoints" +RESULT_DIR = "/eval_results" +LLAMA_CPP_DIR = "/opt/llama.cpp" +LLAMA_SERVER_BIN = f"{LLAMA_CPP_DIR}/build/bin/llama-server" +LLAMA_CONVERT_SCRIPT = f"{LLAMA_CPP_DIR}/convert_hf_to_gguf.py" +MODEL_SERVER_BASE_URL = "http://127.0.0.1:8001/v1" +MODEL_SERVER_HOST = "127.0.0.1" +MODEL_SERVER_PORT = 8001 + + +app = modal.App(APP_NAME) + +checkpoint_volume = modal.Volume.from_name(CHECKPOINT_VOLUME_NAME, create_if_missing=True) +result_volume = modal.Volume.from_name(RESULT_VOLUME_NAME, create_if_missing=True) + +eval_image = ( + modal.Image.from_registry("pytorch/pytorch:2.7.1-cuda12.6-cudnn9-devel") + .apt_install("git", "build-essential", "cmake", "curl", "ninja-build") + .uv_pip_install( + "accelerate>=1.8,<2", + "einops>=0.8,<1", + "ninja>=1.11,<2", + "protobuf>=5,<7", + "safetensors>=0.5,<1", + "sentencepiece>=0.2,<1", + "setuptools>=70", + "torch==2.7.1", + "transformers>=4.52,<5", + "wheel>=0.45", + ) + .add_local_dir("tools/llama.cpp", LLAMA_CPP_DIR, copy=True) + .run_commands( + f"python -m pip install -r {LLAMA_CPP_DIR}/requirements.txt", + f"cmake -S {LLAMA_CPP_DIR} -B {LLAMA_CPP_DIR}/build " + f"-DGGML_CUDA=ON -DLLAMA_CURL=OFF -DCMAKE_BUILD_TYPE=Release " + f"-DCMAKE_CUDA_ARCHITECTURES={DEFAULT_CUDA_ARCHITECTURES}", + f"cmake --build {LLAMA_CPP_DIR}/build --config Release --target llama-server -j $(nproc)", + ) + .env( + { + "TOKENIZERS_PARALLELISM": "false", + "PYTHON_DOTENV_DISABLED": "true", + } + ) + .add_local_python_source("figment", "scripts") +) + + +def build_eval_config( + *, + dataset_version: str = DEFAULT_DATASET_VERSION, + merged_model_name: str = DEFAULT_MERGED_MODEL_NAME, + output_name: str = "", + model_id: str = DEFAULT_MODEL_ID, + timeout_seconds: float = 300.0, + expected_case_count: int = DEFAULT_CASE_COUNT, + max_context_tokens: int = 16384, + max_generation_tokens: int = 1536, +) -> dict[str, Any]: + if not output_name: + stamp = datetime.now(UTC).strftime("%Y%m%dT%H%M%SZ") + output_name = f"{dataset_version}_field_workflow_holdout_modal_gpu_{stamp}" + checkpoint_model_dir = f"{CHECKPOINT_DIR}/{dataset_version}/{merged_model_name}" + return { + "dataset_version": dataset_version, + "merged_model_name": merged_model_name, + "checkpoint_model_dir": checkpoint_model_dir, + "checkpoint_artifact": ( + f"{CHECKPOINT_VOLUME_NAME}:/{dataset_version}/{merged_model_name}" + ), + "result_volume_name": RESULT_VOLUME_NAME, + "output_name": output_name, + "output_dir": f"{RESULT_DIR}/{output_name}", + "gguf_model_path": f"{RESULT_DIR}/model_cache/{dataset_version}/{merged_model_name}.bf16.gguf", + "runtime": "llama_cpp_cuda", + "cuda_architectures": DEFAULT_CUDA_ARCHITECTURES, + "model_id": model_id, + "base_url": MODEL_SERVER_BASE_URL, + "case_paths": [f"/tmp/figment_eval_cases/{Path(DEFAULT_CASE_PATH).name}"], + "timeout_seconds": timeout_seconds, + "expected_case_count": expected_case_count, + "max_context_tokens": max_context_tokens, + "max_generation_tokens": max_generation_tokens, + } + + +@app.function( + image=eval_image, + gpu=DEFAULT_EVAL_GPU, + cpu=8, + memory=131072, + ephemeral_disk=524288, + volumes={ + CHECKPOINT_DIR: checkpoint_volume, + RESULT_DIR: result_volume, + }, + timeout=6 * 60 * 60, +) +def run_batch_eval( + config: dict[str, Any], + case_files: list[dict[str, str]], + protocol_cards: list[dict[str, str]], +) -> dict[str, Any]: + import os + import time + + import torch + + from scripts.run_local_4b_evidence import run_evidence + + started = datetime.now(UTC) + model_dir = Path(str(config["checkpoint_model_dir"])) + output_dir = Path(str(config["output_dir"])) + output_dir.mkdir(parents=True, exist_ok=True) + + if not (model_dir / "config.json").exists(): + raise FileNotFoundError(f"missing merged model config at {model_dir}") + if not (model_dir / "model.safetensors.index.json").exists(): + raise FileNotFoundError(f"missing merged model index at {model_dir}") + + staged_case_paths = _stage_case_files(case_files) + _stage_protocol_cards(protocol_cards) + + runtime_gpu = { + "cuda_available": torch.cuda.is_available(), + "cuda_device_count": torch.cuda.device_count(), + "cuda_device_name": torch.cuda.get_device_name(0) if torch.cuda.is_available() else "", + } + print(json.dumps({"runtime_gpu": runtime_gpu}, sort_keys=True), flush=True) + + gguf_model_path = _ensure_gguf_model(model_dir=model_dir, config=config) + result_volume.commit() + + server = _LlamaCppServer( + gguf_model_path=gguf_model_path, + model_id=str(config["model_id"]), + max_context_tokens=int(config["max_context_tokens"]), + ) + server.start() + try: + summary = run_evidence( + base_url=str(config["base_url"]), + model_id=str(config["model_id"]), + output_dir=output_dir, + case_paths=staged_case_paths, + limit=None, + timeout_seconds=float(config["timeout_seconds"]), + force_eval=True, + ) + finally: + server.stop() + + records_path = output_dir / "local_4b_eval.jsonl" + record_count = _count_jsonl(records_path) + finished = datetime.now(UTC) + manifest = { + "status": "completed" if record_count == int(config["expected_case_count"]) else "count_mismatch", + "config": config, + "runtime_gpu": runtime_gpu, + "checkpoint_artifact": config["checkpoint_artifact"], + "output_volume": RESULT_VOLUME_NAME, + "output_dir": str(output_dir), + "records_path": str(records_path), + "record_count": record_count, + "expected_case_count": int(config["expected_case_count"]), + "started_at": started.isoformat(), + "finished_at": finished.isoformat(), + "runtime_seconds": round(time.monotonic() - server.started_monotonic, 3), + "summary": summary, + "files": sorted(path.name for path in output_dir.iterdir() if path.is_file()), + } + (output_dir / "modal_eval_manifest.json").write_text( + json.dumps(manifest, indent=2, sort_keys=True) + "\n", + encoding="utf-8", + ) + result_volume.commit() + + if record_count != int(config["expected_case_count"]): + raise ValueError(f"expected {config['expected_case_count']} records, found {record_count}") + return manifest + + +def _ensure_gguf_model(*, model_dir: Path, config: dict[str, Any]) -> Path: + import subprocess + import sys + + gguf_path = Path(str(config["gguf_model_path"])) + if gguf_path.exists() and gguf_path.stat().st_size > 0: + print( + json.dumps( + { + "modal_eval_gguf": "reuse_existing", + "path": str(gguf_path), + "bytes": gguf_path.stat().st_size, + }, + sort_keys=True, + ), + flush=True, + ) + return gguf_path + + gguf_path.parent.mkdir(parents=True, exist_ok=True) + command = [ + sys.executable, + LLAMA_CONVERT_SCRIPT, + str(model_dir), + "--outfile", + str(gguf_path), + "--outtype", + "bf16", + ] + print(json.dumps({"modal_eval_gguf": "convert_start", "command": command}, sort_keys=True), flush=True) + completed = subprocess.run( + command, + check=False, + text=True, + stdout=subprocess.PIPE, + stderr=subprocess.STDOUT, + ) + print(completed.stdout, flush=True) + if completed.returncode != 0: + raise RuntimeError(f"GGUF conversion failed with exit code {completed.returncode}") + print( + json.dumps( + { + "modal_eval_gguf": "convert_finished", + "path": str(gguf_path), + "bytes": gguf_path.stat().st_size, + }, + sort_keys=True, + ), + flush=True, + ) + return gguf_path + + +class _LlamaCppServer: + def __init__(self, *, gguf_model_path: Path, model_id: str, max_context_tokens: int) -> None: + self.gguf_model_path = gguf_model_path + self.model_id = model_id + self.max_context_tokens = max_context_tokens + self.process: Any = None + self.started_monotonic = 0.0 + + def start(self) -> None: + import subprocess + import threading + import time + import urllib.request + + command = [ + LLAMA_SERVER_BIN, + "--model", + str(self.gguf_model_path), + "--ctx-size", + str(self.max_context_tokens), + "--host", + MODEL_SERVER_HOST, + "--port", + str(MODEL_SERVER_PORT), + "--alias", + self.model_id, + "--parallel", + "1", + "--temp", + "0", + "--top-p", + "1", + "--reasoning", + "off", + "--n-gpu-layers", + "999", + ] + print(json.dumps({"modal_eval_llama_server": "start", "command": command}, sort_keys=True), flush=True) + self.started_monotonic = time.monotonic() + self.process = subprocess.Popen( + command, + stdout=subprocess.PIPE, + stderr=subprocess.STDOUT, + text=True, + bufsize=1, + ) + threading.Thread(target=self._stream_logs, daemon=True).start() + + deadline = time.monotonic() + 180 + last_error = "" + while time.monotonic() < deadline: + if self.process.poll() is not None: + raise RuntimeError(f"llama-server exited early with code {self.process.returncode}") + try: + with urllib.request.urlopen(f"{MODEL_SERVER_BASE_URL}/models", timeout=2) as response: + if response.status == 200: + print(json.dumps({"modal_eval_llama_server": "ready"}, sort_keys=True), flush=True) + return + except OSError as exc: + last_error = str(exc) + time.sleep(1) + raise RuntimeError(f"llama-server did not become ready: {last_error}") + + def stop(self) -> None: + if self.process is None or self.process.poll() is not None: + return + self.process.terminate() + try: + self.process.wait(timeout=30) + except Exception: + self.process.kill() + self.process.wait(timeout=10) + + def _stream_logs(self) -> None: + if self.process is None or self.process.stdout is None: + return + for line in self.process.stdout: + print(f"[llama-server] {line.rstrip()}", flush=True) + + +class _OpenAICompatibleTransformersServer: + def __init__( + self, + *, + model_dir: Path, + model_id: str, + max_context_tokens: int, + max_generation_tokens: int, + ) -> None: + self.model_dir = model_dir + self.model_id = model_id + self.max_context_tokens = max_context_tokens + self.max_generation_tokens = max_generation_tokens + self.httpd: Any = None + self.thread: Any = None + self.started_monotonic = 0.0 + + def start(self) -> None: + import threading + import time + import urllib.request + from http.server import ThreadingHTTPServer + + model_runtime = _TransformersRuntime( + model_dir=self.model_dir, + model_id=self.model_id, + max_context_tokens=self.max_context_tokens, + max_generation_tokens=self.max_generation_tokens, + ) + handler = _handler_factory(model_runtime) + self.httpd = ThreadingHTTPServer((MODEL_SERVER_HOST, MODEL_SERVER_PORT), handler) + self.thread = threading.Thread(target=self.httpd.serve_forever, daemon=True) + self.started_monotonic = time.monotonic() + self.thread.start() + deadline = time.monotonic() + 30 + last_error = "" + while time.monotonic() < deadline: + try: + with urllib.request.urlopen(f"{MODEL_SERVER_BASE_URL}/models", timeout=2) as response: + if response.status == 200: + return + except OSError as exc: + last_error = str(exc) + time.sleep(0.25) + raise RuntimeError(f"model server did not become ready: {last_error}") + + def stop(self) -> None: + if self.httpd is not None: + self.httpd.shutdown() + self.httpd.server_close() + if self.thread is not None: + self.thread.join(timeout=10) + + +class _TransformersRuntime: + def __init__( + self, + *, + model_dir: Path, + model_id: str, + max_context_tokens: int, + max_generation_tokens: int, + ) -> None: + import threading + + import torch + from transformers import AutoModelForCausalLM + from transformers import AutoTokenizer + + self.model_id = model_id + self.max_context_tokens = max_context_tokens + self.max_generation_tokens = max_generation_tokens + self.lock = threading.Lock() + self.request_count = 0 + self.torch = torch + self.tokenizer = AutoTokenizer.from_pretrained( + model_dir, + trust_remote_code=True, + local_files_only=True, + ) + if self.tokenizer.pad_token is None: + self.tokenizer.pad_token = self.tokenizer.eos_token + self.model = AutoModelForCausalLM.from_pretrained( + model_dir, + trust_remote_code=True, + local_files_only=True, + dtype=torch.bfloat16, + ) + if torch.cuda.is_available(): + self.model.to("cuda") + self.model.eval() + self.model.config.use_cache = True + + def models_payload(self) -> dict[str, Any]: + return { + "object": "list", + "data": [ + { + "id": self.model_id, + "object": "model", + "owned_by": "figment-modal-batch", + } + ], + } + + def chat_completion(self, body: dict[str, Any]) -> dict[str, Any]: + import time + import uuid + + messages = body.get("messages") + if not isinstance(messages, list): + raise ValueError("messages must be a list") + requested_max_tokens = int(body.get("max_tokens") or 1024) + with self.lock: + self.request_count += 1 + request_index = self.request_count + started = time.monotonic() + input_ids = self.tokenizer.apply_chat_template( + messages, + add_generation_prompt=True, + return_tensors="pt", + ) + device = next(self.model.parameters()).device + input_ids = input_ids.to(device) + input_len = int(input_ids.shape[-1]) + available_tokens = max(128, self.max_context_tokens - input_len - 8) + max_new_tokens = max(1, min(requested_max_tokens, available_tokens, self.max_generation_tokens)) + print( + json.dumps( + { + "modal_eval_request": request_index, + "status": "started", + "prompt_tokens": input_len, + "max_new_tokens": max_new_tokens, + }, + sort_keys=True, + ), + flush=True, + ) + attention_mask = self.torch.ones_like(input_ids) + with self.torch.inference_mode(): + output_ids = self.model.generate( + input_ids=input_ids, + attention_mask=attention_mask, + max_new_tokens=max_new_tokens, + do_sample=False, + pad_token_id=self.tokenizer.pad_token_id, + eos_token_id=self.tokenizer.eos_token_id, + ) + generated_ids = output_ids[0, input_len:] + content = self.tokenizer.decode(generated_ids, skip_special_tokens=True).strip() + print( + json.dumps( + { + "modal_eval_request": request_index, + "status": "finished", + "completion_tokens": int(generated_ids.numel()), + "elapsed_seconds": round(time.monotonic() - started, 3), + }, + sort_keys=True, + ), + flush=True, + ) + return { + "id": f"chatcmpl-{uuid.uuid4().hex}", + "object": "chat.completion", + "created": int(time.time()), + "model": self.model_id, + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": content}, + "finish_reason": "stop", + } + ], + "usage": { + "prompt_tokens": input_len, + "completion_tokens": int(generated_ids.numel()), + "total_tokens": input_len + int(generated_ids.numel()), + }, + } + + +def _handler_factory(runtime: _TransformersRuntime) -> Any: + import json + from http.server import BaseHTTPRequestHandler + + class Handler(BaseHTTPRequestHandler): + def do_GET(self) -> None: # noqa: N802 + if self.path.rstrip("/") == "/v1/models": + self._send_json(200, runtime.models_payload()) + else: + self._send_json(404, {"error": f"unknown path: {self.path}"}) + + def do_POST(self) -> None: # noqa: N802 + if self.path.rstrip("/") != "/v1/chat/completions": + self._send_json(404, {"error": f"unknown path: {self.path}"}) + return + try: + length = int(self.headers.get("Content-Length", "0")) + body = json.loads(self.rfile.read(length).decode("utf-8")) + payload = runtime.chat_completion(body) + except Exception as exc: # pragma: no cover - exercised inside Modal runtime. + self._send_json(500, {"error": str(exc)}) + return + self._send_json(200, payload) + + def log_message(self, format: str, *args: Any) -> None: + return + + def _send_json(self, status: int, payload: dict[str, Any]) -> None: + encoded = json.dumps(payload).encode("utf-8") + self.send_response(status) + self.send_header("Content-Type", "application/json") + self.send_header("Content-Length", str(len(encoded))) + self.end_headers() + self.wfile.write(encoded) + + return Handler + + +def _stage_case_files(case_files: list[dict[str, str]]) -> list[Path]: + case_dir = Path("/tmp/figment_eval_cases") + case_dir.mkdir(parents=True, exist_ok=True) + paths: list[Path] = [] + for item in case_files: + path = case_dir / Path(item["name"]).name + path.write_text(item["text"], encoding="utf-8") + paths.append(path) + return paths + + +def _stage_protocol_cards(protocol_cards: list[dict[str, str]]) -> None: + from figment import retrieval + + card_dir = Path(retrieval.DEFAULT_CARD_DIR) + card_dir.mkdir(parents=True, exist_ok=True) + for path in card_dir.glob("*.json"): + path.unlink() + for item in protocol_cards: + (card_dir / Path(item["name"]).name).write_text(item["text"], encoding="utf-8") + + +def _count_jsonl(path: Path) -> int: + if not path.exists(): + return 0 + return sum(1 for line in path.read_text(encoding="utf-8").splitlines() if line.strip()) + + +def _read_case_files(paths: list[str]) -> list[dict[str, str]]: + return [ + {"name": Path(path).name, "text": Path(path).read_text(encoding="utf-8")} + for path in paths + ] + + +def _read_protocol_cards() -> list[dict[str, str]]: + return [ + {"name": path.name, "text": path.read_text(encoding="utf-8")} + for path in sorted(Path("data/protocol_cards").glob("*.json")) + ] + + +@app.local_entrypoint() +def main( + output_name: str = "", + dataset_version: str = DEFAULT_DATASET_VERSION, + merged_model_name: str = DEFAULT_MERGED_MODEL_NAME, + cases: str = DEFAULT_CASE_PATH, + timeout_seconds: float = 300.0, + gpu: str = DEFAULT_EVAL_GPU, +) -> None: + case_paths = [item.strip() for item in cases.split(",") if item.strip()] + config = build_eval_config( + dataset_version=dataset_version, + merged_model_name=merged_model_name, + output_name=output_name, + timeout_seconds=timeout_seconds, + ) + if len(case_paths) != 1 or Path(case_paths[0]).name != Path(DEFAULT_CASE_PATH).name: + config["case_paths"] = [f"/tmp/figment_eval_cases/{Path(path).name}" for path in case_paths] + config["expected_case_count"] = sum( + 1 for path in case_paths for line in Path(path).read_text(encoding="utf-8").splitlines() if line.strip() + ) + + result = run_batch_eval.with_options(gpu=gpu).remote( + config, + _read_case_files(case_paths), + _read_protocol_cards(), + ) + print(json.dumps({"modal_batch_eval": result}, indent=2, sort_keys=True)) diff --git a/modal/finetune_figment_nemotron.py b/modal/finetune_figment_nemotron.py new file mode 100644 index 0000000000000000000000000000000000000000..cc555894067f0d3fc32ec18e41d752a367a51aa5 --- /dev/null +++ b/modal/finetune_figment_nemotron.py @@ -0,0 +1,581 @@ +"""Modal LoRA fine-tuning job for Figment's local Nemotron 4B navigator. + +Run a smoke job first: + + .venv/bin/modal run modal/finetune_figment_nemotron.py --smoke true + +Then run the full pilot: + + .venv/bin/modal run modal/finetune_figment_nemotron.py +""" + +from __future__ import annotations + +import json +from pathlib import Path +from typing import Any + +import modal + + +APP_NAME = "figment-nemotron-4b-lora" +DEFAULT_DATASET_VERSION = "figment_sft_v1" +DEFAULT_BASE_MODEL_ID = "nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16" +DEFAULT_DATASET_PATH = "data/finetune/figment_sft_v1.jsonl" +DEFAULT_TRAIN_GPU = "H100" +DATA_VOLUME_NAME = "figment-sft-data" +MODEL_CACHE_VOLUME_NAME = "figment-model-cache" +CHECKPOINT_VOLUME_NAME = "figment-checkpoints" +DATA_DIR = "/data" +MODEL_CACHE_DIR = "/model_cache" +CHECKPOINT_DIR = "/checkpoints" + + +app = modal.App(APP_NAME) + +model_cache_volume = modal.Volume.from_name(MODEL_CACHE_VOLUME_NAME, create_if_missing=True) +data_volume = modal.Volume.from_name(DATA_VOLUME_NAME, create_if_missing=True) +checkpoint_volume = modal.Volume.from_name(CHECKPOINT_VOLUME_NAME, create_if_missing=True) +huggingface_secret = modal.Secret.from_name("huggingface-token", required_keys=["HF_TOKEN"]) + +training_image = ( + modal.Image.from_registry("pytorch/pytorch:2.7.1-cuda12.6-cudnn9-devel") + .apt_install("git", "build-essential", "ninja-build") + .uv_pip_install( + "accelerate>=1.8,<2", + "datasets>=3.6,<5", + "einops>=0.8,<1", + "ninja>=1.11,<2", + "peft>=0.15,<1", + "protobuf>=5,<7", + "safetensors>=0.5,<1", + "sentencepiece>=0.2,<1", + "setuptools>=70", + "torch==2.7.1", + "transformers>=4.52,<5", + "wandb>=0.19,<1", + "wheel>=0.45", + ) + .run_commands( + "python -m pip install --no-build-isolation --no-deps " + "'causal-conv1d==1.6.2.post1' 'mamba-ssm==2.2.6.post3'" + ) + .env( + { + "HF_HOME": MODEL_CACHE_DIR, + "HF_HUB_CACHE": f"{MODEL_CACHE_DIR}/hub", + "HF_XET_HIGH_PERFORMANCE": "1", + "TOKENIZERS_PARALLELISM": "false", + } + ) +) + + +def dataset_volume_paths(dataset_version: str) -> dict[str, str]: + root = f"{DATA_DIR}/{dataset_version}" + return { + "root": root, + "train": f"{root}/train.jsonl", + "validation": f"{root}/validation.jsonl", + "manifest": f"{root}/manifest.json", + } + + +def build_train_config( + *, + dataset_version: str = DEFAULT_DATASET_VERSION, + base_model_id: str = DEFAULT_BASE_MODEL_ID, + output_name: str = "pilot-lora", + resume_adapter_name: str = "", + resume_adapter_dataset_version: str = "", + smoke: bool = False, + max_steps: int = 40, + max_seq_length: int = 16384, + learning_rate: float = 1e-4, + lora_r: int = 16, + lora_alpha: int = 32, + lora_dropout: float = 0.05, + gradient_accumulation_steps: int = 8, + validation_steps: int = 25, + save_steps: int = 50, +) -> dict[str, Any]: + if smoke: + max_steps = max(1, min(max_steps, 5)) + max_seq_length = max(512, min(max_seq_length, 2048)) + if not output_name.endswith("-smoke"): + output_name = f"{output_name}-smoke" + + return { + "dataset_version": dataset_version, + "base_model_id": base_model_id, + "output_name": output_name, + "output_dir": f"{CHECKPOINT_DIR}/{dataset_version}/{output_name}", + "resume_adapter_name": resume_adapter_name, + "resume_adapter_dataset_version": resume_adapter_dataset_version or dataset_version, + "resume_adapter_dir": ( + f"{CHECKPOINT_DIR}/{resume_adapter_dataset_version or dataset_version}/{resume_adapter_name}" + if resume_adapter_name + else "" + ), + "max_steps": max_steps, + "max_seq_length": max_seq_length, + "learning_rate": learning_rate, + "lora_r": lora_r, + "lora_alpha": lora_alpha, + "lora_dropout": lora_dropout, + "gradient_accumulation_steps": gradient_accumulation_steps, + "per_device_train_batch_size": 1, + "per_device_eval_batch_size": 1, + "validation_steps": max(1, min(validation_steps, max_steps)), + "save_steps": max(1, min(save_steps, max_steps)), + "warmup_ratio": 0.05, + "weight_decay": 0.0, + "seed": 42, + "smoke": smoke, + } + + +def build_merge_config( + *, + dataset_version: str = DEFAULT_DATASET_VERSION, + base_model_id: str = DEFAULT_BASE_MODEL_ID, + adapter_name: str, + output_name: str = "", +) -> dict[str, Any]: + if not output_name: + output_name = f"{adapter_name}-merged-bf16" + return { + "dataset_version": dataset_version, + "base_model_id": base_model_id, + "adapter_name": adapter_name, + "adapter_dir": f"{CHECKPOINT_DIR}/{dataset_version}/{adapter_name}", + "output_name": output_name, + "output_dir": f"{CHECKPOINT_DIR}/{dataset_version}/{output_name}", + } + + +@app.function( + image=training_image, + volumes={DATA_DIR: data_volume}, + timeout=30 * 60, +) +def stage_dataset(dataset_version: str, train_jsonl: str, validation_jsonl: str, manifest_json: str) -> dict[str, Any]: + paths = dataset_volume_paths(dataset_version) + root = Path(paths["root"]) + root.mkdir(parents=True, exist_ok=True) + Path(paths["train"]).write_text(train_jsonl, encoding="utf-8") + Path(paths["validation"]).write_text(validation_jsonl, encoding="utf-8") + Path(paths["manifest"]).write_text(manifest_json, encoding="utf-8") + data_volume.commit() + return { + "dataset_version": dataset_version, + "train_path": paths["train"], + "validation_path": paths["validation"], + "manifest_path": paths["manifest"], + "train_rows": _count_jsonl_text(train_jsonl), + "validation_rows": _count_jsonl_text(validation_jsonl), + } + + +@app.function( + image=training_image, + gpu=DEFAULT_TRAIN_GPU, + cpu=8, + memory=65536, + ephemeral_disk=524288, + volumes={ + DATA_DIR: data_volume, + MODEL_CACHE_DIR: model_cache_volume, + CHECKPOINT_DIR: checkpoint_volume, + }, + secrets=[huggingface_secret], + timeout=12 * 60 * 60, +) +def train(config: dict[str, Any]) -> dict[str, Any]: + import inspect + import os + + import torch + from datasets import Dataset + from peft import LoraConfig + from peft import PeftModel + from peft import TaskType + from peft import get_peft_model + from transformers import AutoModelForCausalLM + from transformers import AutoTokenizer + from transformers import DataCollatorForSeq2Seq + from transformers import Trainer + from transformers import TrainingArguments + + runtime_gpu = { + "cuda_available": torch.cuda.is_available(), + "cuda_device_count": torch.cuda.device_count(), + "cuda_device_name": torch.cuda.get_device_name(0) if torch.cuda.is_available() else "", + } + print(json.dumps({"runtime_gpu": runtime_gpu}, sort_keys=True), flush=True) + + paths = dataset_volume_paths(str(config["dataset_version"])) + train_rows = _read_jsonl(Path(paths["train"])) + validation_rows = _read_jsonl(Path(paths["validation"])) + if not train_rows: + raise ValueError(f"no training rows staged at {paths['train']}") + if not validation_rows: + raise ValueError(f"no validation rows staged at {paths['validation']}") + + token = os.environ["HF_TOKEN"] + base_model_id = str(config["base_model_id"]) + tokenizer = AutoTokenizer.from_pretrained( + base_model_id, + cache_dir=MODEL_CACHE_DIR, + token=token, + trust_remote_code=True, + ) + if tokenizer.pad_token is None: + tokenizer.pad_token = tokenizer.eos_token + tokenizer.padding_side = "right" + + train_dataset = _tokenized_dataset(train_rows, tokenizer, int(config["max_seq_length"])) + validation_dataset = _tokenized_dataset(validation_rows, tokenizer, int(config["max_seq_length"])) + if len(train_dataset) == 0: + raise ValueError("all training rows lost supervised assistant tokens after tokenization") + if len(validation_dataset) == 0: + raise ValueError("all validation rows lost supervised assistant tokens after tokenization") + + model = AutoModelForCausalLM.from_pretrained( + base_model_id, + cache_dir=MODEL_CACHE_DIR, + token=token, + trust_remote_code=True, + dtype=torch.bfloat16, + ) + model.config.use_cache = False + model.gradient_checkpointing_enable() + + resume_adapter_dir = str(config.get("resume_adapter_dir") or "") + if resume_adapter_dir: + if not Path(resume_adapter_dir).exists(): + raise ValueError(f"resume adapter not found at {resume_adapter_dir}") + model = PeftModel.from_pretrained( + model, + resume_adapter_dir, + is_trainable=True, + ) + else: + lora_config = LoraConfig( + r=int(config["lora_r"]), + lora_alpha=int(config["lora_alpha"]), + lora_dropout=float(config["lora_dropout"]), + bias="none", + task_type=TaskType.CAUSAL_LM, + target_modules="all-linear", + ) + model = get_peft_model(model, lora_config) + model.print_trainable_parameters() + + output_dir = str(config["output_dir"]) + Path(output_dir).mkdir(parents=True, exist_ok=True) + args_kwargs = { + "output_dir": output_dir, + "per_device_train_batch_size": int(config["per_device_train_batch_size"]), + "per_device_eval_batch_size": int(config["per_device_eval_batch_size"]), + "gradient_accumulation_steps": int(config["gradient_accumulation_steps"]), + "learning_rate": float(config["learning_rate"]), + "max_steps": int(config["max_steps"]), + "warmup_ratio": float(config["warmup_ratio"]), + "weight_decay": float(config["weight_decay"]), + "logging_steps": 1, + "save_steps": int(config["save_steps"]), + "eval_steps": int(config["validation_steps"]), + "bf16": True, + "fp16": False, + "gradient_checkpointing": True, + "remove_unused_columns": False, + "report_to": [], + "seed": int(config["seed"]), + } + if "eval_strategy" in inspect.signature(TrainingArguments.__init__).parameters: + args_kwargs["eval_strategy"] = "steps" + else: + args_kwargs["evaluation_strategy"] = "steps" + training_args = TrainingArguments(**args_kwargs) + + trainer = Trainer( + model=model, + args=training_args, + train_dataset=train_dataset, + eval_dataset=validation_dataset, + tokenizer=tokenizer, + data_collator=DataCollatorForSeq2Seq( + tokenizer=tokenizer, + model=model, + padding=True, + label_pad_token_id=-100, + ), + ) + train_result = trainer.train() + trainer.save_model(output_dir) + tokenizer.save_pretrained(output_dir) + + metrics = dict(train_result.metrics) + manifest = { + "config": _safe_config(config), + "train_rows": len(train_rows), + "validation_rows": len(validation_rows), + "tokenized_train_rows": len(train_dataset), + "tokenized_validation_rows": len(validation_dataset), + "metrics": metrics, + "adapter_path": output_dir, + "runtime_gpu": runtime_gpu, + } + Path(output_dir, "figment_training_manifest.json").write_text( + json.dumps(manifest, indent=2, sort_keys=True) + "\n", + encoding="utf-8", + ) + checkpoint_volume.commit() + model_cache_volume.commit() + return manifest + + +@app.function( + image=training_image, + gpu=DEFAULT_TRAIN_GPU, + cpu=8, + memory=65536, + ephemeral_disk=524288, + volumes={ + MODEL_CACHE_DIR: model_cache_volume, + CHECKPOINT_DIR: checkpoint_volume, + }, + secrets=[huggingface_secret], + timeout=4 * 60 * 60, +) +def merge_adapter(config: dict[str, Any]) -> dict[str, Any]: + import os + + import torch + from peft import PeftModel + from transformers import AutoModelForCausalLM + from transformers import AutoTokenizer + + token = os.environ["HF_TOKEN"] + base_model_id = str(config["base_model_id"]) + adapter_dir = Path(str(config["adapter_dir"])) + output_dir = Path(str(config["output_dir"])) + if not (adapter_dir / "adapter_config.json").exists(): + raise FileNotFoundError(f"missing adapter_config.json in {adapter_dir}") + if not (adapter_dir / "adapter_model.safetensors").exists(): + raise FileNotFoundError(f"missing adapter_model.safetensors in {adapter_dir}") + + tokenizer = AutoTokenizer.from_pretrained( + adapter_dir, + cache_dir=MODEL_CACHE_DIR, + token=token, + trust_remote_code=True, + ) + model = AutoModelForCausalLM.from_pretrained( + base_model_id, + cache_dir=MODEL_CACHE_DIR, + token=token, + trust_remote_code=True, + dtype=torch.bfloat16, + device_map="auto", + ) + peft_model = PeftModel.from_pretrained(model, adapter_dir, is_trainable=False) + merged_model = peft_model.merge_and_unload(safe_merge=True) + merged_model.config.use_cache = True + if getattr(merged_model, "generation_config", None) is not None: + merged_model.generation_config.do_sample = False + merged_model.generation_config.top_p = None + merged_model.generation_config.temperature = None + output_dir.mkdir(parents=True, exist_ok=True) + merged_model.save_pretrained( + output_dir, + safe_serialization=True, + max_shard_size="4GB", + ) + tokenizer.save_pretrained(output_dir) + + files = sorted(path.name for path in output_dir.iterdir() if path.is_file()) + manifest = { + "base_model_id": base_model_id, + "adapter_dir": str(adapter_dir), + "output_dir": str(output_dir), + "files": files, + "dtype": "bfloat16", + "merge_method": "peft.merge_and_unload(safe_merge=True)", + } + (output_dir / "figment_merge_manifest.json").write_text( + json.dumps(manifest, indent=2, sort_keys=True) + "\n", + encoding="utf-8", + ) + checkpoint_volume.commit() + model_cache_volume.commit() + return manifest + + +@app.local_entrypoint() +def main( + dataset_version: str = DEFAULT_DATASET_VERSION, + dataset: str = DEFAULT_DATASET_PATH, + prepared_dir: str = "", + output_name: str = "pilot-lora", + resume_adapter_name: str = "", + resume_adapter_dataset_version: str = "", + smoke: bool = False, + skip_stage: bool = False, + max_steps: int = 40, + max_seq_length: int = 16384, + learning_rate: float = 1e-4, + lora_r: int = 16, + lora_alpha: int = 32, + lora_dropout: float = 0.05, + gradient_accumulation_steps: int = 8, + validation_steps: int = 25, + save_steps: int = 50, + gpu: str = DEFAULT_TRAIN_GPU, + merge_only: bool = False, + adapter_name: str = "pilot-20260608", + merged_name: str = "", + spawn_train: bool = False, +) -> None: + if merge_only: + merge_config = build_merge_config( + dataset_version=dataset_version, + adapter_name=adapter_name, + output_name=merged_name, + ) + merge_result = merge_adapter.with_options(gpu=gpu).remote(merge_config) + print(json.dumps({"merge": merge_result}, indent=2, sort_keys=True)) + return + + config = build_train_config( + dataset_version=dataset_version, + output_name=output_name, + resume_adapter_name=resume_adapter_name, + resume_adapter_dataset_version=resume_adapter_dataset_version, + smoke=smoke, + max_steps=max_steps, + max_seq_length=max_seq_length, + learning_rate=learning_rate, + lora_r=lora_r, + lora_alpha=lora_alpha, + lora_dropout=lora_dropout, + gradient_accumulation_steps=gradient_accumulation_steps, + validation_steps=validation_steps, + save_steps=save_steps, + ) + config["requested_gpu"] = gpu + + if not skip_stage: + from scripts.prepare_modal_finetune_dataset import prepare_dataset + + output_dir = Path(prepared_dir) if prepared_dir else Path("data/finetune/modal") / dataset_version + manifest = prepare_dataset( + dataset_path=Path(dataset), + output_dir=output_dir, + dataset_version=dataset_version, + ) + stage_result = stage_dataset.remote( + dataset_version, + Path(manifest["train_path"]).read_text(encoding="utf-8"), + Path(manifest["validation_path"]).read_text(encoding="utf-8"), + json.dumps(manifest, indent=2, sort_keys=True) + "\n", + ) + print(json.dumps({"stage_dataset": stage_result}, indent=2, sort_keys=True)) + + train_function = train.with_options(gpu=gpu) + if spawn_train: + train_call = train_function.spawn(config) + print( + json.dumps( + { + "train_spawned": { + "function_call_id": train_call.object_id, + "dashboard_url": train_call.get_dashboard_url(), + "dataset_version": dataset_version, + "output_name": output_name, + "resume_adapter_name": resume_adapter_name, + "resume_adapter_dataset_version": resume_adapter_dataset_version, + "max_steps": max_steps, + "learning_rate": learning_rate, + "lora_r": lora_r, + "lora_alpha": lora_alpha, + "lora_dropout": lora_dropout, + "gradient_accumulation_steps": gradient_accumulation_steps, + "validation_steps": config["validation_steps"], + "save_steps": config["save_steps"], + "gpu": gpu, + } + }, + indent=2, + sort_keys=True, + ) + ) + return + + train_result = train_function.remote(config) + print(json.dumps({"train": train_result}, indent=2, sort_keys=True)) + + +def _tokenized_dataset(rows: list[dict[str, Any]], tokenizer: Any, max_seq_length: int) -> Any: + from datasets import Dataset + + tokenized = [] + skipped = 0 + for row in rows: + item = _tokenize_row(row, tokenizer, max_seq_length) + if item is None: + skipped += 1 + continue + tokenized.append(item) + if skipped: + print(f"Skipped {skipped} rows with no supervised assistant tokens after truncation") + return Dataset.from_list(tokenized) + + +def _tokenize_row(row: dict[str, Any], tokenizer: Any, max_seq_length: int) -> dict[str, list[int]] | None: + messages = row["messages"] + prompt_messages = [messages[0]] + if getattr(tokenizer, "chat_template", None): + prompt_text = tokenizer.apply_chat_template( + prompt_messages, + tokenize=False, + add_generation_prompt=True, + ) + full_text = tokenizer.apply_chat_template( + messages, + tokenize=False, + add_generation_prompt=False, + ) + else: + prompt_text = f"User:\n{messages[0]['content']}\n\nAssistant:\n" + full_text = f"{prompt_text}{messages[1]['content']}{getattr(tokenizer, 'eos_token', '') or ''}" + + full_ids = tokenizer(full_text, add_special_tokens=False)["input_ids"] + prompt_ids = tokenizer(prompt_text, add_special_tokens=False)["input_ids"] + if len(full_ids) > max_seq_length: + cut = len(full_ids) - max_seq_length + input_ids = full_ids[cut:] + else: + cut = 0 + input_ids = full_ids + labels = list(input_ids) + mask_until = max(0, min(len(prompt_ids) - cut, len(labels))) + for index in range(mask_until): + labels[index] = -100 + if not any(label != -100 for label in labels): + return None + attention_mask = [1] * len(input_ids) + return {"input_ids": input_ids, "attention_mask": attention_mask, "labels": labels} + + +def _read_jsonl(path: Path) -> list[dict[str, Any]]: + return [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()] + + +def _count_jsonl_text(value: str) -> int: + return sum(1 for line in value.splitlines() if line.strip()) + + +def _safe_config(config: dict[str, Any]) -> dict[str, Any]: + return {key: value for key, value in config.items() if "token" not in key.lower() and "secret" not in key.lower()} diff --git a/modal/upload_checkpoint_to_hf.py b/modal/upload_checkpoint_to_hf.py new file mode 100644 index 0000000000000000000000000000000000000000..9457d10273837ab66f6e31a274ba22d6166fb3b7 --- /dev/null +++ b/modal/upload_checkpoint_to_hf.py @@ -0,0 +1,120 @@ +"""Upload a checkpoint folder from a Modal volume to Hugging Face. + +This is intended for large merged model artifacts that should move directly +from Modal storage to the Hub without first pulling the full checkpoint local. +""" + +from __future__ import annotations + +import json +from pathlib import Path +from typing import Any + +import modal + + +APP_NAME = "figment-checkpoint-hf-upload" +CHECKPOINT_VOLUME_NAME = "figment-checkpoints" +CHECKPOINT_DIR = "/checkpoints" +DEFAULT_REPO_ID = "build-small-hackathon/figment-finetuned-model-archive" + + +app = modal.App(APP_NAME) + +checkpoint_volume = modal.Volume.from_name(CHECKPOINT_VOLUME_NAME, create_if_missing=False) +huggingface_secret = modal.Secret.from_name("huggingface-token", required_keys=["HF_TOKEN"]) + +upload_image = ( + modal.Image.debian_slim(python_version="3.12") + .uv_pip_install("huggingface_hub>=1.18,<2") + .env({"HF_XET_HIGH_PERFORMANCE": "1"}) +) + + +@app.function( + image=upload_image, + cpu=4, + memory=16384, + ephemeral_disk=524288, + volumes={CHECKPOINT_DIR: checkpoint_volume}, + secrets=[huggingface_secret], + timeout=6 * 60 * 60, +) +def upload_checkpoint(config: dict[str, Any]) -> dict[str, Any]: + from huggingface_hub import HfApi + + dataset_version = str(config["dataset_version"]) + checkpoint_name = str(config["checkpoint_name"]) + repo_id = str(config["repo_id"]) + repo_type = str(config.get("repo_type") or "model") + path_in_repo = str(config.get("path_in_repo") or f"{dataset_version}/{checkpoint_name}").strip("/") + commit_message = str(config.get("commit_message") or f"Upload {dataset_version} {checkpoint_name}") + private = bool(config.get("private", False)) + required_files = list(config.get("required_files") or []) + + checkpoint_dir = Path(CHECKPOINT_DIR) / dataset_version / checkpoint_name + if not checkpoint_dir.exists(): + raise FileNotFoundError(f"checkpoint directory does not exist: {checkpoint_dir}") + if not checkpoint_dir.is_dir(): + raise NotADirectoryError(f"checkpoint path is not a directory: {checkpoint_dir}") + + missing = [name for name in required_files if not (checkpoint_dir / name).exists()] + if missing: + raise FileNotFoundError(f"checkpoint is missing required files: {missing}") + + api = HfApi() + api.create_repo(repo_id=repo_id, repo_type=repo_type, private=private, exist_ok=True) + commit_info = api.upload_folder( + folder_path=str(checkpoint_dir), + repo_id=repo_id, + repo_type=repo_type, + path_in_repo=path_in_repo, + commit_message=commit_message, + ) + + files = sorted(path.name for path in checkpoint_dir.iterdir() if path.is_file()) + result = { + "status": "uploaded", + "checkpoint_volume": CHECKPOINT_VOLUME_NAME, + "checkpoint_dir": str(checkpoint_dir), + "repo_id": repo_id, + "repo_type": repo_type, + "path_in_repo": path_in_repo, + "commit_message": commit_message, + "commit_url": getattr(commit_info, "commit_url", ""), + "commit_oid": getattr(commit_info, "oid", ""), + "files": files, + "required_files": required_files, + } + print(json.dumps({"hf_checkpoint_upload": result}, sort_keys=True), flush=True) + return result + + +@app.local_entrypoint() +def main( + dataset_version: str, + checkpoint_name: str, + repo_id: str = DEFAULT_REPO_ID, + path_in_repo: str = "", + commit_message: str = "", + private: bool = False, +) -> None: + config = { + "dataset_version": dataset_version, + "checkpoint_name": checkpoint_name, + "repo_id": repo_id, + "repo_type": "model", + "path_in_repo": path_in_repo or f"{dataset_version}/{checkpoint_name}", + "commit_message": commit_message or f"Upload {dataset_version} {checkpoint_name}", + "private": private, + "required_files": [ + "config.json", + "model.safetensors.index.json", + "tokenizer.json", + "tokenizer_config.json", + "chat_template.jinja", + "figment_merge_manifest.json", + ], + } + result = upload_checkpoint.remote(config) + print(json.dumps({"upload": result}, indent=2, sort_keys=True)) diff --git a/scripts/audit_submission_claims.py b/scripts/audit_submission_claims.py new file mode 100644 index 0000000000000000000000000000000000000000..75eb08d6167ab77654a03f69ea845ac530242fe7 --- /dev/null +++ b/scripts/audit_submission_claims.py @@ -0,0 +1,286 @@ +#!/usr/bin/env python3 +"""Audit Figment submission copy for evidence-gated claim drift.""" + +from __future__ import annotations + +import argparse +from dataclasses import dataclass +import json +from pathlib import Path +import re +import sys +from typing import Any + + +REPO_ROOT = Path(__file__).resolve().parents[1] + +AUDITED_FILES = ( + Path("README.md"), + Path("docs/submission_checklist.md"), + Path("docs/safety_statement.md"), + Path("docs/local_llama_eval_evidence.md"), + Path("docs/local_parakeet_asr_evidence.md"), + Path("docs/user_test_notes.md"), +) + +SAFE_CONTEXT_RE = re.compile( + r"\b(" + r"proof[- ]needed|not yet proven|not proven|unproven|pending|targeted|stretch|tentative|" + r"not proof|is not proof|not ready|not demo[- ]visible|artifact availability is not proof|" + r"until|before|after|once|only if|only after|if .* proven|requires?|needed|" + r"do not|must not|cannot|does not|artifact presence alone|template only|no completed|" + r"no outcome recorded|claim only|claiming" + r")\b", + re.IGNORECASE, +) + + +@dataclass(frozen=True) +class ClaimGate: + key: str + label: str + evidence_summary: str + patterns: tuple[re.Pattern[str], ...] + + +CLAIM_GATES = ( + ClaimGate( + key="off_grid", + label="Off the Grid / no-cloud", + evidence_summary="recorded no-cloud trace or completed local evidence bundle", + patterns=( + re.compile(r"\bOff the Grid\b.*\b(achieved|proven|validated|ready|complete|eligible)\b", re.IGNORECASE), + re.compile(r"\boff[- ]grid\b.*\b(achieved|proven|validated|ready|complete)\b", re.IGNORECASE), + re.compile(r"\bno[- ]cloud\b.*\b(achieved|proven|validated|ready|complete)\b", re.IGNORECASE), + ), + ), + ClaimGate( + key="llama_champion", + label="Llama Champion", + evidence_summary="eligible llama.cpp/local route trace or eval evidence", + patterns=( + re.compile(r"\bLlama Champion\b.*\b(achieved|proven|validated|ready|complete|eligible)\b", re.IGNORECASE), + re.compile(r"\bllama\.cpp\b.*\b(achieved|proven|validated|ready|complete|eligible)\b", re.IGNORECASE), + ), + ), + ClaimGate( + key="well_tuned", + label="Well-Tuned", + evidence_summary="published tuned model or adapter used by the app and measured", + patterns=( + re.compile(r"\bWell[- ]Tuned\b.*\b(achieved|proven|validated|ready|complete|eligible)\b", re.IGNORECASE), + re.compile(r"\b(fine[- ]tuned|adapter|LoRA)\b.*\b(published|used by the app|measured improvement|achieved)\b", re.IGNORECASE), + ), + ), + ClaimGate( + key="backyard_user_use", + label="Backyard AI user-use", + evidence_summary="completed trained-responder user-test notes", + patterns=( + re.compile(r"\b(responder|participant|target user|volunteer)\b.*\b(used|tested|validated|approved|endorsed)\b", re.IGNORECASE), + re.compile(r"\b(used|tested|validated|approved|endorsed)\b.*\b(Figment|prototype|app)\b", re.IGNORECASE), + ), + ), + ClaimGate( + key="local_asr", + label="Local Parakeet ASR", + evidence_summary="local ASR provider payload with counts_as_local_asr_proof=true", + patterns=( + re.compile(r"\bParakeet\b.*\b(proven|validated|ready|demo[- ]visible|enabled|passes|green)\b", re.IGNORECASE), + re.compile(r"\blocal ASR\b.*\b(proven|validated|ready|demo[- ]visible|enabled|passes|green)\b", re.IGNORECASE), + ), + ), + ClaimGate( + key="local_4b", + label="Local 4B model competence", + evidence_summary="50-case local eval with configured-model competence", + patterns=( + re.compile(r"\blocal 4B\b.*\b(proven|validated|ready|competence|passed|green|achieved)\b", re.IGNORECASE), + re.compile(r"\blocal endpoint\b.*\b(proven|validated|ready|competence|passed|green|achieved)\b", re.IGNORECASE), + ), + ), + ClaimGate( + key="demo_video", + label="Demo video", + evidence_summary="final demo video link", + patterns=( + re.compile(r"\bdemo video\b.*\b(complete|published|posted|final|https?://)\b", re.IGNORECASE), + ), + ), + ClaimGate( + key="social_post", + label="Social post", + evidence_summary="final social post link", + patterns=( + re.compile(r"\bsocial post\b.*\b(complete|published|posted|final|https?://)\b", re.IGNORECASE), + ), + ), +) + + +def audit_claims(repo_root: Path = REPO_ROOT, files: tuple[Path, ...] = AUDITED_FILES) -> dict[str, Any]: + gate_status = evidence_gate_status(repo_root) + violations = scan_claims(repo_root, files, gate_status) + return { + "status": "passed" if not violations else "failed", + "repo_root": str(repo_root), + "gate_status": gate_status, + "audited_files": [str(path) for path in files], + "violations": violations, + } + + +def evidence_gate_status(repo_root: Path = REPO_ROOT) -> dict[str, bool]: + return { + "off_grid": _has_no_cloud_evidence(repo_root), + "llama_champion": _has_local_4b_competence(repo_root), + "well_tuned": _has_well_tuned_evidence(repo_root), + "backyard_user_use": _has_user_test_notes(repo_root), + "local_asr": _has_local_asr_proof(repo_root), + "local_4b": _has_local_4b_competence(repo_root), + "demo_video": _checklist_row_has_final_link(repo_root, "Demo video"), + "social_post": _checklist_row_has_final_link(repo_root, "Social post"), + } + + +def scan_claims(repo_root: Path, files: tuple[Path, ...], gate_status: dict[str, bool]) -> list[dict[str, Any]]: + violations: list[dict[str, Any]] = [] + for relative_path in files: + path = repo_root / relative_path + if not path.exists(): + continue + for line_number, line in enumerate(path.read_text(encoding="utf-8").splitlines(), start=1): + violations.extend(_line_violations(relative_path, line_number, line, gate_status)) + return violations + + +def scan_text( + text: str, + *, + relative_path: Path = Path("sample.md"), + gate_status: dict[str, bool] | None = None, +) -> list[dict[str, Any]]: + states = gate_status or {gate.key: False for gate in CLAIM_GATES} + violations: list[dict[str, Any]] = [] + for line_number, line in enumerate(text.splitlines(), start=1): + violations.extend(_line_violations(relative_path, line_number, line, states)) + return violations + + +def _line_violations( + relative_path: Path, + line_number: int, + line: str, + gate_status: dict[str, bool], +) -> list[dict[str, Any]]: + if SAFE_CONTEXT_RE.search(line): + return [] + found: list[dict[str, Any]] = [] + for gate in CLAIM_GATES: + if gate_status.get(gate.key) is True: + continue + for pattern in gate.patterns: + if pattern.search(line): + found.append( + { + "file": str(relative_path), + "line": line_number, + "gate": gate.key, + "claim": gate.label, + "required_evidence": gate.evidence_summary, + "text": line.strip(), + } + ) + break + return found + + +def _has_local_4b_competence(repo_root: Path) -> bool: + for summary_path in repo_root.glob("traces/local_4b_evidence_*/summary.json"): + summary = _read_json(summary_path) + if ( + summary.get("counts_as_50_case_local_llm_competence") is True + and int(summary.get("total_cases") or 0) >= 50 + ): + return True + return False + + +def _has_local_asr_proof(repo_root: Path) -> bool: + for summary_path in repo_root.glob("traces/local_asr_parakeet_evidence_*/summary.json"): + summary = _read_json(summary_path) + if summary.get("counts_as_local_asr_proof") is True: + return True + return False + + +def _has_no_cloud_evidence(repo_root: Path) -> bool: + for summary_path in repo_root.glob("traces/local_4b_evidence_*/summary.json"): + summary = _read_json(summary_path) + if summary.get("counts_as_no_cloud_route_proof") is True: + return True + return False + + +def _has_well_tuned_evidence(repo_root: Path) -> bool: + ledger = (repo_root / "docs/model_parameter_evidence_ledger.md").read_text(encoding="utf-8") + return ( + "published fine-tuned model" in ledger.lower() + and "not trained, published, or measured" not in ledger.lower() + ) + + +def _has_user_test_notes(repo_root: Path) -> bool: + path = repo_root / "docs/user_test_notes.md" + if not path.exists(): + return False + text = path.read_text(encoding="utf-8").lower() + if "template only" in text or "no outcome recorded" in text: + return False + return "pending" not in text + + +def _checklist_row_has_final_link(repo_root: Path, artifact_label: str) -> bool: + path = repo_root / "docs/submission_checklist.md" + if not path.exists(): + return False + marker = f"| {artifact_label} |" + for line in path.read_text(encoding="utf-8").splitlines(): + if marker in line: + lowered = line.lower() + return "http" in lowered and "pending" not in lowered and "proof needed" not in lowered + return False + + +def _read_json(path: Path) -> dict[str, Any]: + try: + payload = json.loads(path.read_text(encoding="utf-8")) + except (OSError, json.JSONDecodeError): + return {} + return payload if isinstance(payload, dict) else {} + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--repo-root", type=Path, default=REPO_ROOT) + parser.add_argument("--json", action="store_true", help="Print full JSON report.") + args = parser.parse_args(argv) + + report = audit_claims(args.repo_root.resolve()) + if args.json: + print(json.dumps(report, indent=2, sort_keys=True)) + elif report["violations"]: + print("submission claim audit failed:", file=sys.stderr) + for violation in report["violations"]: + print( + f"{violation['file']}:{violation['line']}: {violation['claim']} needs " + f"{violation['required_evidence']}: {violation['text']}", + file=sys.stderr, + ) + else: + print("submission claim audit passed") + return 0 if report["status"] == "passed" else 1 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/augment_finetune_repair_rows.py b/scripts/augment_finetune_repair_rows.py new file mode 100644 index 0000000000000000000000000000000000000000..47e2a35da45e92817abc2b2967f3c6cd28866a16 --- /dev/null +++ b/scripts/augment_finetune_repair_rows.py @@ -0,0 +1,416 @@ +"""Add focused-repair SFT rows that match Figment's local 4B harness.""" + +from __future__ import annotations + +import argparse +from collections import Counter +from datetime import UTC +from datetime import datetime +import hashlib +import json +from pathlib import Path +import sys +from typing import Any, Callable + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from figment.focused_repair import build_focused_repair_prompts # noqa: E402 +from figment.observation_targets import required_observation_targets # noqa: E402 +from figment.prompt_builder import build_prompt # noqa: E402 +from figment.retrieval import known_card_ids # noqa: E402 +from figment.retrieval import load_protocol_cards # noqa: E402 +from figment.retrieval import query_from_intake # noqa: E402 +from figment.retrieval import search_protocol_cards # noqa: E402 +from figment.rules import run_red_flag_checks # noqa: E402 +from figment.trace import stable_hash # noqa: E402 +from figment.validators import urgency_floor_from_rules # noqa: E402 +from figment.validators import validate_navigator_output # noqa: E402 +from scripts.generate_finetune_data import SAFETY_CARD_ID # noqa: E402 +from scripts.generate_finetune_data import SBAR_CARD_ID # noqa: E402 +from scripts.generate_finetune_data import _required_retrieved_ids # noqa: E402 +from scripts.generate_finetune_data import ensure_retrieved_cards # noqa: E402 +from scripts.generate_finetune_data import uses_v7_source_card_policy # noqa: E402 +from scripts.generate_finetune_data import v7_source_card_closure_issues # noqa: E402 + + +DATASET_PATH = Path("data/finetune/figment_sft_v1.jsonl") +CASE_SPEC_PATH = Path("data/finetune/figment_sft_v1_case_specs.jsonl") +MANIFEST_PATH = Path("data/finetune/figment_sft_v1_manifest.json") +REPAIR_SCOPES = ( + "missing_observations", + "citations_and_pathways", + "handoff_note_sbar", + "forbidden_clinical_language", + "protocol_urgency", + "schema", +) +V2_REPAIR_SCOPE_DISTRIBUTION = ( + ("handoff_note_sbar", 100), + ("missing_observations", 100), + ("citations_and_pathways", 75), + ("forbidden_clinical_language", 50), + ("schema", 50), + ("protocol_urgency", 25), +) +V3_REPAIR_SCOPE_DISTRIBUTION = ( + ("handoff_note_sbar", 120), + ("missing_observations", 110), + ("citations_and_pathways", 90), + ("forbidden_clinical_language", 60), + ("protocol_urgency", 60), + ("schema", 60), +) +V4_REPAIR_SCOPE_DISTRIBUTION = ( + ("handoff_note_sbar", 45), + ("citations_and_pathways", 25), + ("missing_observations", 15), + ("forbidden_clinical_language", 5), + ("protocol_urgency", 5), + ("schema", 5), +) +V5_REPAIR_SCOPE_DISTRIBUTION = ( + ("missing_observations", 55), + ("handoff_note_sbar", 45), + ("citations_and_pathways", 35), + ("forbidden_clinical_language", 25), + ("protocol_urgency", 20), + ("schema", 20), +) +V6_REPAIR_SCOPE_DISTRIBUTION = ( + ("missing_observations", 250), +) +V7_REPAIR_SCOPE_DISTRIBUTION = ( + ("source_card_closure", 160), + ("source_card_negative_correction", 50), + ("observation_patch_repair", 30), +) +V7_SOURCE_REPAIR_SCOPES = {"source_card_closure", "source_card_negative_correction"} + + +def dataset_paths(dataset_version: str) -> dict[str, Path]: + root = Path("data/finetune") + return { + "dataset": root / f"{dataset_version}.jsonl", + "case_specs": root / f"{dataset_version}_case_specs.jsonl", + "manifest": root / f"{dataset_version}_manifest.json", + } + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--dataset-version", default="figment_sft_v1") + parser.add_argument("--dataset", type=Path, default=None) + parser.add_argument("--case-specs", type=Path, default=None) + parser.add_argument("--manifest", type=Path, default=None) + parser.add_argument("--repair-count", type=int, default=60) + args = parser.parse_args(argv) + paths = dataset_paths(args.dataset_version) + args.dataset = args.dataset or paths["dataset"] + args.case_specs = args.case_specs or paths["case_specs"] + args.manifest = args.manifest or paths["manifest"] + + rows = _read_jsonl(args.dataset) + specs = {str(item["case_id"]): item for item in _read_jsonl(args.case_specs)} + existing_ids = {str(row.get("case_id")) for row in rows} + base_rows = [row for row in rows if row.get("metadata", {}).get("task_type", "navigator_full") == "navigator_full"] + repair_rows: list[dict[str, Any]] = [] + skipped: Counter[str] = Counter() + + for scope_name in _scope_schedule(args.repair_count, dataset_version=args.dataset_version): + created = None + for base_row in base_rows: + candidate = build_repair_row(base_row, specs[str(base_row["case_id"])], scope_name) + if candidate is None: + continue + if candidate["case_id"] in existing_ids: + continue + created = candidate + break + if created is None: + skipped[scope_name] += 1 + continue + repair_rows.append(created) + rows.append(created) + existing_ids.add(created["case_id"]) + + args.dataset.write_text("".join(json.dumps(row, sort_keys=True) + "\n" for row in rows), encoding="utf-8") + update_manifest(args.manifest, args.dataset, args.case_specs, rows, repair_rows, skipped) + print( + json.dumps( + { + "base_rows": len(base_rows), + "repair_rows_added": len(repair_rows), + "total_rows": len(rows), + "repair_scope_counts": dict(Counter(row["metadata"]["repair_scope"] for row in repair_rows)), + "skipped": dict(skipped), + }, + indent=2, + sort_keys=True, + ) + ) + return 0 + + +def build_repair_row(base_row: dict[str, Any], spec: dict[str, Any], scope_name: str) -> dict[str, Any] | None: + intake = spec["structured_intake"] + rule_results = [rule.to_dict() for rule in run_red_flag_checks(intake)] + floor = urgency_floor_from_rules(rule_results) + retrieved = search_protocol_cards(query_from_intake(intake), limit=6) + spec_dataset_version = str(spec.get("dataset_version") or base_row.get("version") or "") + if uses_v7_source_card_policy(spec_dataset_version): + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + synthetic_spec = type( + "SyntheticSpecForRepairGeneration", + (), + { + "target_protocol_card_id": str(spec.get("target_protocol_card_id") or ""), + "dataset_version": spec_dataset_version, + }, + )() + retrieved = ensure_retrieved_cards( + retrieved, + required_ids=_required_retrieved_ids(synthetic_spec, rule_results), + cards_by_id=cards_by_id, + limit=6, + ) + retrieved_ids = [str(item.get("card_id", "")) for item in retrieved if item.get("card_id")] + original_prompt, prompt_hash = build_prompt(intake, retrieved, rule_results, floor) + gold_output = json.loads(base_row["messages"][1]["content"]) + previous_output = _corrupt_output(gold_output, scope_name, floor) + if previous_output is None: + return None + validation = validate_navigator_output( + previous_output, + known_card_ids(), + urgency_floor=floor, + confirmed_intake=intake, + rule_results=rule_results, + retrieved_card_ids=set(retrieved_ids), + retrieved_cards=retrieved, + strict_schema=True, + ).to_dict() + failures = validation.get("failures") or [] + extra_failures = _extra_failures_for_scope(previous_output, spec, scope_name) + failures = list(failures) + extra_failures + if validation.get("passed") is True and not extra_failures: + return None + if not failures: + return None + focused_prompts = build_focused_repair_prompts( + original_prompt=original_prompt, + previous_output=previous_output, + failures=failures, + urgency_floor=floor, + required_observation_targets=required_observation_targets(retrieved), + ) + focused_prompt = next((item for item in focused_prompts if item.scope.name == scope_name), None) + if focused_prompt is None: + return None + target = {field: gold_output[field] for field in focused_prompt.scope.fields if field in gold_output} + if set(target) != set(focused_prompt.scope.fields): + return None + base_case_id = str(base_row["case_id"]) + case_id = f"{base_case_id}--repair-{scope_name}" + return { + "case_id": case_id, + "uuid": case_id, + "license": base_row.get("license", "synthetic internal training data"), + "generator": base_row.get("generator"), + "version": base_row.get("version", "figment_sft_v1"), + "category": f"focused_repair:{scope_name}", + "reasoning": "off", + "messages": [ + {"role": "user", "content": focused_prompt.prompt}, + {"role": "assistant", "content": json.dumps(target, sort_keys=True)}, + ], + "tags": sorted(set(base_row.get("tags", [])) | {"focused_repair", scope_name}), + "metadata": { + **base_row.get("metadata", {}), + "task_type": "focused_repair", + "base_case_id": base_case_id, + "base_failure_class": base_row.get("metadata", {}).get("failure_class", base_row.get("category")), + "failure_class": f"focused_repair:{scope_name}", + "repair_scope": scope_name, + "repair_fields": list(focused_prompt.scope.fields), + "validation_failures": failures, + "previous_output_hash": stable_hash(previous_output), + "prompt_hash": stable_hash(focused_prompt.prompt), + "prompt_template_hash": prompt_hash, + "retrieved_card_ids": retrieved_ids, + "teacher_label_mode": "teacher_gold_subset_focused_repair_harness_prompt", + "expected_action": { + "repair_scope": scope_name, + "repair_fields": list(focused_prompt.scope.fields), + "base_case_id": base_case_id, + }, + "reward_components": { + "repair_prompt_matches_harness": 1, + "allowed_fields_only": 1, + "target_fields_from_teacher_gold": 1, + "no_visible_reasoning": 1, + }, + "pass_rate_total": 1, + "pass_rate_passed": 1, + "raw_teacher_output_hash": base_row.get("metadata", {}).get("raw_teacher_output_hash"), + "generated_at": datetime.now(UTC).isoformat(), + }, + } + + +def _corrupt_output(output: dict[str, Any], scope_name: str, floor: str) -> dict[str, Any] | None: + corrupted = json.loads(json.dumps(output)) + if scope_name == "missing_observations": + corrupted["missing_info_to_collect"] = ["repeat vitals"] + corrupted["next_observations_to_collect"] = ["repeat vitals"] + elif scope_name == "citations_and_pathways": + corrupted["source_cards"] = [] + corrupted["candidate_protocol_pathways"] = [{"card_id": "NOT-A-CARD", "reason_relevant": "bad citation"}] + elif scope_name == "handoff_note_sbar": + corrupted["handoff_note_sbar"] = { + "situation": "unsupported rash oxygen pregnancy finding", + "background": "", + "assessment_observations_only": "", + "handoff_request": "", + } + elif scope_name == "forbidden_clinical_language": + corrupted["responder_checklist"] = ["Diagnose the condition, prescribe medication, and discharge home."] + elif scope_name == "protocol_urgency": + if floor == "routine": + return None + corrupted["protocol_urgency"] = "routine" + elif scope_name == "schema": + corrupted.pop("safety_boundary", None) + corrupted.pop("responder_plain_language_script", None) + elif scope_name == "source_card_closure": + source_cards = [str(card_id) for card_id in corrupted.get("source_cards", []) if str(card_id)] + corrupted["source_cards"] = [card_id for card_id in source_cards if card_id not in {SAFETY_CARD_ID, SBAR_CARD_ID}] + elif scope_name == "source_card_negative_correction": + source_cards = [str(card_id) for card_id in corrupted.get("source_cards", []) if str(card_id)] + for distractor in ("PED-DEHYD-RED-FLAGS-v1", "WOUND-INFECTION-ESCALATION-v1", "FEVER-RED-FLAGS-v1"): + if distractor not in source_cards: + source_cards.append(distractor) + break + corrupted["source_cards"] = source_cards + elif scope_name == "observation_patch_repair": + corrupted["missing_info_to_collect"] = ["source card ids", "deterministic rule results", "navigator validation result"] + corrupted["next_observations_to_collect"] = list(corrupted["missing_info_to_collect"]) + else: + return None + return corrupted + + +def _extra_failures_for_scope(previous_output: dict[str, Any], spec: dict[str, Any], scope_name: str) -> list[str]: + if scope_name == "source_card_closure": + target = str(spec.get("target_protocol_card_id") or "") + issues = v7_source_card_closure_issues(previous_output, target_protocol_card_id=target) + return [f"source_card_closure:{issue}" for issue in issues] + if scope_name == "source_card_negative_correction": + return ["source_card_negative_correction:remove irrelevant or disallowed source card"] + if scope_name == "observation_patch_repair": + return ["observation_patch_repair:replace scaffold-owned observation fields"] + return [] + + +def _scope_schedule(count: int, *, dataset_version: str = "figment_sft_v1") -> list[str]: + if dataset_version.startswith("figment_sft_v7"): + return _weighted_scope_schedule(count, V7_REPAIR_SCOPE_DISTRIBUTION) + if dataset_version.startswith("figment_sft_v6"): + return _weighted_scope_schedule(count, V6_REPAIR_SCOPE_DISTRIBUTION) + if dataset_version.startswith("figment_sft_v5"): + return _weighted_scope_schedule(count, V5_REPAIR_SCOPE_DISTRIBUTION) + if dataset_version.startswith("figment_sft_v4"): + return _weighted_scope_schedule(count, V4_REPAIR_SCOPE_DISTRIBUTION) + if dataset_version.startswith("figment_sft_v3"): + return _weighted_scope_schedule(count, V3_REPAIR_SCOPE_DISTRIBUTION) + if dataset_version == "figment_sft_v2": + return _weighted_scope_schedule(count, V2_REPAIR_SCOPE_DISTRIBUTION) + schedule = [] + while len(schedule) < count: + schedule.extend(REPAIR_SCOPES) + return schedule[:count] + + +def _weighted_scope_schedule(count: int, distribution: tuple[tuple[str, int], ...]) -> list[str]: + if count <= 0: + return [] + total_weight = sum(weight for _, weight in distribution) + targets: dict[str, int] = {} + fractions: list[tuple[float, int, str]] = [] + for order, (scope, weight) in enumerate(distribution): + exact = count * weight / total_weight + targets[scope] = int(exact) + fractions.append((exact - int(exact), -order, scope)) + for _, _, scope in sorted(fractions, reverse=True)[: count - sum(targets.values())]: + targets[scope] += 1 + + produced: Counter[str] = Counter() + schedule: list[str] = [] + scope_order = {scope: index for index, (scope, _) in enumerate(distribution)} + while len(schedule) < count: + remaining_scopes = [scope for scope, target in targets.items() if produced[scope] < target] + scope = max( + remaining_scopes, + key=lambda item: ( + (targets[item] - produced[item]) / targets[item], + -scope_order[item], + ), + ) + schedule.append(scope) + produced[scope] += 1 + return schedule + + +def update_manifest( + manifest_path: Path, + dataset_path: Path, + case_specs_path: Path, + rows: list[dict[str, Any]], + repair_rows: list[dict[str, Any]], + skipped: Counter[str], +) -> None: + manifest = json.loads(manifest_path.read_text(encoding="utf-8")) if manifest_path.exists() else {} + task_counts = Counter(row.get("metadata", {}).get("task_type", "navigator_full") for row in rows) + category_counts = Counter(str(row.get("category", "")) for row in rows) + repair_scope_counts = Counter( + row.get("metadata", {}).get("repair_scope") + for row in rows + if row.get("metadata", {}).get("task_type") == "focused_repair" + ) + manifest.update( + { + "row_count": len(rows), + "output_sha256": _file_sha256(dataset_path), + "case_specs_sha256": _file_sha256(case_specs_path), + "task_type_counts": dict(sorted(task_counts.items())), + "category_counts": dict(sorted(category_counts.items())), + "repair_scope_counts": { + str(key): value for key, value in sorted(repair_scope_counts.items()) if key + }, + "focused_repair_rows_added": len(repair_rows), + "focused_repair_skipped": dict(skipped), + "harness_task_coverage": { + "navigator_full": task_counts.get("navigator_full", 0), + "focused_repair": task_counts.get("focused_repair", 0), + "audio_field_draft": "not a 4B chat-completion task in this harness; Parakeet/provider payload plus deterministic field drafting", + }, + } + ) + manifest_path.write_text(json.dumps(manifest, indent=2, sort_keys=True) + "\n", encoding="utf-8") + + +def _read_jsonl(path: Path) -> list[dict[str, Any]]: + return [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()] + + +def _file_sha256(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as file: + for chunk in iter(lambda: file.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/build_corrected_field_workflow_holdout.py b/scripts/build_corrected_field_workflow_holdout.py new file mode 100644 index 0000000000000000000000000000000000000000..bc1ef012cf035d11775b5c316c5352ce6fc1eb71 --- /dev/null +++ b/scripts/build_corrected_field_workflow_holdout.py @@ -0,0 +1,250 @@ +"""Build a corrected scoring view for the frozen field-workflow holdout. + +The original holdout file remains frozen. This script preserves case IDs and +structured intakes, then recomputes expected labels with the current rule and +prompt-building code. +""" + +from __future__ import annotations + +import argparse +from datetime import UTC, datetime +import hashlib +import json +from pathlib import Path +import sys +from typing import Any + + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from figment.prompt_builder import build_prompt # noqa: E402 +from figment.retrieval import query_from_intake # noqa: E402 +from figment.retrieval import load_protocol_cards # noqa: E402 +from figment.retrieval import search_protocol_cards # noqa: E402 +from figment.rules import run_red_flag_checks # noqa: E402 +from figment.validators import urgency_floor_from_rules # noqa: E402 +from scripts.generate_finetune_data import stable_hash # noqa: E402 + + +BASE_VERSION = "field_workflow_holdout_v1" +DERIVED_VERSION = "field_workflow_holdout_v1_corrected_scoring" +DEFAULT_INPUT_PATH = Path("data/eval/field_workflow_holdout_v1.jsonl") +DEFAULT_OUTPUT_PATH = Path("data/eval/field_workflow_holdout_v1_corrected_scoring.jsonl") +DEFAULT_MANIFEST_PATH = Path("data/eval/field_workflow_holdout_v1_corrected_scoring_manifest.json") +RULE_CARD_IDS = { + "AMS-001": "AMS-RED-FLAGS-v1", + "RESP-001": "RESP-DISTRESS-RED-FLAGS-v1", + "PREG-001": "PREG-DANGER-SIGNS-v1", + "red_flag_chest_pain": "CHEST-PAIN-ESCALATION-v1", + "STROKE-001": "STROKE-SIGNS-v1", + "PED-DEHYD-001": "PED-DEHYD-RED-FLAGS-v1", + "FEVER-001": "FEVER-RED-FLAGS-v1", + "WOUND-001": "WOUND-INFECTION-ESCALATION-v1", +} + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--input", type=Path, default=DEFAULT_INPUT_PATH) + parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT_PATH) + parser.add_argument("--manifest", type=Path, default=DEFAULT_MANIFEST_PATH) + args = parser.parse_args(argv) + + manifest = build_corrected_view(input_path=args.input, output_path=args.output, manifest_path=args.manifest) + print(json.dumps(manifest, indent=2, sort_keys=True)) + return 0 + + +def build_corrected_view(*, input_path: Path, output_path: Path, manifest_path: Path) -> dict[str, Any]: + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + input_rows = _load_jsonl(input_path) + output_rows: list[dict[str, Any]] = [] + row_hashes: list[dict[str, str]] = [] + changed_cases: list[dict[str, Any]] = [] + + for row in input_rows: + corrected = _correct_row(row, cards_by_id) + output_rows.append(corrected) + row_hashes.append({"case_id": corrected["case_id"], "sha256": _json_sha256(corrected)}) + diff = _label_diff(row, corrected) + if diff: + changed_cases.append({"case_id": corrected["case_id"], "changes": diff}) + + output_path.parent.mkdir(parents=True, exist_ok=True) + output_path.write_text( + "".join(json.dumps(row, sort_keys=True) + "\n" for row in output_rows), + encoding="utf-8", + ) + + manifest = { + "dataset_version": DERIVED_VERSION, + "derived_from_dataset_version": BASE_VERSION, + "source_path": str(input_path), + "source_sha256": _file_sha256(input_path), + "output_path": str(output_path), + "output_sha256": _file_sha256(output_path), + "row_count": len(output_rows), + "changed_case_count": len(changed_cases), + "changed_cases": changed_cases, + "generated_at": datetime.now(UTC).isoformat(), + "source_generator": "scripts/build_corrected_field_workflow_holdout.py", + "policy": { + "preserve_frozen_holdout_file": True, + "preserve_case_ids": True, + "recompute_expected_labels_with_current_rules": True, + }, + "row_hashes": row_hashes, + } + manifest_path.parent.mkdir(parents=True, exist_ok=True) + manifest_path.write_text(json.dumps(manifest, indent=2, sort_keys=True) + "\n", encoding="utf-8") + return manifest + + +def _correct_row(row: dict[str, Any], cards_by_id: dict[str, dict[str, Any]]) -> dict[str, Any]: + intake = dict(row["structured_intake"]) + rule_results = [rule.to_dict() for rule in run_red_flag_checks(intake)] + urgency_floor = urgency_floor_from_rules(rule_results) + retrieved = search_protocol_cards(query_from_intake(intake), limit=6) + retrieved_ids = [str(item.get("card_id", "")) for item in retrieved if item.get("card_id")] + prompt, prompt_template_hash = build_prompt(intake, retrieved, rule_results, urgency_floor) + + expected_red_flags = [str(rule["rule_id"]) for rule in rule_results] + current_rule_ids = {str(rule.get("rule_id")) for rule in rule_results if rule.get("rule_id")} + removed_rule_cards = _removed_rule_cards(row, current_rule_ids) + expected_source_cards = _correct_expected_source_cards( + row, + rule_results, + retrieved_ids, + removed_rule_cards=removed_rule_cards, + ) + expected_missing = _remove_required_observations_for_removed_rule_cards( + row, + expected_source_cards=expected_source_cards, + cards_by_id=cards_by_id, + removed_rule_cards=removed_rule_cards, + ) + + corrected = dict(row) + corrected.update( + { + "dataset_version": DERIVED_VERSION, + "base_dataset_version": str(row.get("dataset_version") or BASE_VERSION), + "expected_red_flag_rule_ids": expected_red_flags, + "expected_min_protocol_urgency": urgency_floor, + "expected_source_card_ids": expected_source_cards, + "expected_missing_observations": expected_missing, + "retrieved_card_ids": retrieved_ids, + "workflow_priority_observations": expected_missing[:5], + "prompt_hash": stable_hash(prompt), + "prompt_template_hash": prompt_template_hash, + } + ) + for key in ( + "expected_model_observation_cues", + "expected_handoff_cues", + "expected_harness_evidence_cues", + ): + corrected.pop(key, None) + return corrected + + +def _correct_expected_source_cards( + row: dict[str, Any], + rule_results: list[dict[str, Any]], + retrieved_ids: list[str], + *, + removed_rule_cards: set[str], +) -> list[str]: + expected = [str(card_id) for card_id in row.get("expected_source_card_ids", []) if str(card_id)] + target_card_id = str(row.get("target_protocol_card_id") or "") + current_rule_cards = {str(rule.get("card_id")) for rule in rule_results if rule.get("card_id")} + + corrected = [ + card_id + for card_id in expected + if card_id not in removed_rule_cards or card_id == target_card_id or card_id in current_rule_cards + ] + for card_id in current_rule_cards: + if card_id in retrieved_ids and card_id not in corrected: + corrected.append(card_id) + return corrected + + +def _remove_required_observations_for_removed_rule_cards( + row: dict[str, Any], + *, + expected_source_cards: list[str], + cards_by_id: dict[str, dict[str, Any]], + removed_rule_cards: set[str], +) -> list[str]: + if not removed_rule_cards: + return [str(item) for item in row.get("expected_missing_observations", []) if str(item)] + + removed_required: set[str] = set() + for card_id in removed_rule_cards: + removed_required.update(_required_observations(cards_by_id.get(card_id, {}))) + + remaining_required: set[str] = set() + for card_id in expected_source_cards: + remaining_required.update(_required_observations(cards_by_id.get(card_id, {}))) + + corrected: list[str] = [] + for cue in [str(item) for item in row.get("expected_missing_observations", []) if str(item)]: + if cue in removed_required and cue not in remaining_required: + continue + corrected.append(cue) + return corrected + + +def _removed_rule_cards(row: dict[str, Any], current_rule_ids: set[str]) -> set[str]: + old_rule_ids = {str(item) for item in row.get("expected_red_flag_rule_ids", [])} + return _removed_rule_cards_from_ids(old_rule_ids=old_rule_ids, new_rule_ids=current_rule_ids) + + +def _removed_rule_cards_from_ids(*, old_rule_ids: set[str], new_rule_ids: set[str]) -> set[str]: + return {RULE_CARD_IDS[rule_id] for rule_id in old_rule_ids - new_rule_ids if rule_id in RULE_CARD_IDS} + + +def _required_observations(card: dict[str, Any]) -> set[str]: + values = card.get("required_observations") + if not isinstance(values, list): + return set() + return {str(item) for item in values if str(item)} + + +def _label_diff(before: dict[str, Any], after: dict[str, Any]) -> dict[str, Any]: + diff: dict[str, Any] = {} + keys = ( + "expected_red_flag_rule_ids", + "expected_min_protocol_urgency", + "expected_source_card_ids", + "expected_candidate_pathway_card_ids", + "expected_missing_observations", + ) + for key in keys: + if before.get(key) != after.get(key): + diff[key] = {"before": before.get(key), "after": after.get(key)} + return diff + + +def _load_jsonl(path: Path) -> list[dict[str, Any]]: + return [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()] + + +def _json_sha256(value: dict[str, Any]) -> str: + return "sha256:" + hashlib.sha256(json.dumps(value, sort_keys=True).encode("utf-8")).hexdigest() + + +def _file_sha256(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as file: + for chunk in iter(lambda: file.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/build_v6_replay_corpus.py b/scripts/build_v6_replay_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..9d4b2551d89b8ba49750d5f99b4452b6edc9e19a --- /dev/null +++ b/scripts/build_v6_replay_corpus.py @@ -0,0 +1,441 @@ +"""Audit v3-v5 SFT rows and select clean replay rows for Figment v6.""" + +from __future__ import annotations + +import argparse +from collections import Counter, defaultdict +from dataclasses import dataclass +import hashlib +import json +from pathlib import Path +import random +import sys +from typing import Any + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + + +DEFAULT_INPUTS = [ + Path("data/finetune/figment_sft_v5.jsonl"), + Path("data/finetune/figment_sft_v4.jsonl"), + Path("data/finetune/figment_sft_v3.jsonl"), +] +DEFAULT_OUTPUT = Path("data/finetune/figment_sft_v6_replay.jsonl") +DEFAULT_MANIFEST = Path("data/finetune/figment_sft_v6_replay_manifest.json") +DEFAULT_TARGETS = { + "figment_sft_v5": 450, + "figment_sft_v4": 300, + "figment_sft_v3": 150, +} +DEFAULT_SEED = "figment-sft-v6-replay-selection" + +HARNESS_METADATA_CUES = { + "source card ids", + "source protocol card ids", + "retrieved protocol card ids", + "deterministic rule results", + "navigator validation result", + "confirmed intake status", + "manual correction status for audio-derived fields", +} + +GENERIC_OBSERVATION_PHRASES = { + "monitor closely", + "collect more information", + "follow up", + "assess patient", + "repeat vitals", +} + +UNSAFE_OBSERVATION_FRAGMENTS = { + "diagnose", + "prescribe", + "dose", + "discharge", + "send home", + "clear for discharge", + "start medication", +} + +OBSERVATION_FOCUSED_CATEGORIES = { + "missing_observation_prioritization", + "required_observation_id_selection", + "focused_repair:missing_observations", +} + +CATEGORY_PRIORITY = { + "focused_repair:handoff_note_sbar": 100, + "focused_repair:citations_and_pathways": 95, + "focused_repair:protocol_urgency": 90, + "focused_repair:schema": 85, + "source_card_invariant": 80, + "sbar_observation_ownership": 78, + "general_regression": 76, + "noisy_field_audio_style": 74, + "radio_handoff": 72, + "sbar_handoff_usefulness": 70, + "source_card_discipline": 68, + "low_resource_constraints": 66, + "rural_clinic_intake": 64, + "disaster_triage": 62, +} + + +@dataclass(frozen=True) +class AuditResult: + accepted: bool + reasons: tuple[str, ...] + score: int + + +@dataclass(frozen=True) +class Candidate: + row: dict[str, Any] + source_path: str + source_dataset_version: str + category: str + task_type: str + audit: AuditResult + ordinal: int + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--input", type=Path, action="append", default=None, help="Input JSONL corpus path") + parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT) + parser.add_argument("--manifest", type=Path, default=DEFAULT_MANIFEST) + parser.add_argument("--seed", default=DEFAULT_SEED) + for dataset_version, target in DEFAULT_TARGETS.items(): + parser.add_argument(f"--{dataset_version.replace('_', '-')}-target", type=int, default=target) + args = parser.parse_args(argv) + + input_paths = args.input or DEFAULT_INPUTS + targets = { + "figment_sft_v5": args.figment_sft_v5_target, + "figment_sft_v4": args.figment_sft_v4_target, + "figment_sft_v3": args.figment_sft_v3_target, + } + summary = build_replay_corpus( + input_paths=input_paths, + output_path=args.output, + manifest_path=args.manifest, + targets=targets, + seed=args.seed, + ) + print(json.dumps(summary, indent=2, sort_keys=True)) + return 0 if summary["selected_rows"] > 0 else 1 + + +def build_replay_corpus( + *, + input_paths: list[Path], + output_path: Path, + manifest_path: Path, + targets: dict[str, int], + seed: str = DEFAULT_SEED, +) -> dict[str, Any]: + candidates: list[Candidate] = [] + rejected: Counter[str] = Counter() + source_row_counts: Counter[str] = Counter() + input_hashes: dict[str, str] = {} + + for input_path in input_paths: + input_hashes[str(input_path)] = _sha256_path(input_path) + for ordinal, row in enumerate(_read_jsonl(input_path), start=1): + source_version = _source_dataset_version(row, input_path) + source_row_counts[source_version] += 1 + audit = audit_row(row) + category = _category(row) + task_type = _task_type(row) + if audit.accepted: + candidates.append( + Candidate( + row=row, + source_path=str(input_path), + source_dataset_version=source_version, + category=category, + task_type=task_type, + audit=audit, + ordinal=ordinal, + ) + ) + else: + for reason in audit.reasons: + rejected[f"{source_version}:{reason}"] += 1 + + selected = select_candidates(candidates, targets=targets, seed=seed) + rows = [_annotate_row(candidate) for candidate in selected] + _write_jsonl(output_path, rows) + + manifest = { + "dataset_version": "figment_sft_v6_replay", + "selection_policy_version": 1, + "seed": seed, + "input_paths": [str(path) for path in input_paths], + "input_sha256": input_hashes, + "source_row_counts": dict(sorted(source_row_counts.items())), + "target_rows_by_source_dataset_version": dict(sorted(targets.items())), + "accepted_candidate_rows": len(candidates), + "selected_rows": len(selected), + "selected_sha256": _sha256_path(output_path), + "output_path": str(output_path), + "rejected_reason_counts": dict(sorted(rejected.items())), + "selected_by_source_dataset_version": dict( + sorted(Counter(candidate.source_dataset_version for candidate in selected).items()) + ), + "selected_by_category": dict(sorted(Counter(candidate.category for candidate in selected).items())), + "selected_by_task_type": dict(sorted(Counter(candidate.task_type for candidate in selected).items())), + "shortage_by_source_dataset_version": _shortages(selected, targets), + "policy_notes": [ + "Rows are direct replay candidates only; rejected rows should not be used without rewriting.", + "Duplicate long missing/next observation lists are rejected.", + "Harness metadata cues in observation fields are rejected.", + "Observation-focused full rows must carry selected_required_observation_ids.", + "The selector does not fill quotas with rows that fail v6 replay policy.", + ], + } + manifest_path.parent.mkdir(parents=True, exist_ok=True) + manifest_path.write_text(json.dumps(manifest, indent=2, sort_keys=True) + "\n", encoding="utf-8") + return manifest + + +def audit_row(row: dict[str, Any]) -> AuditResult: + reasons: list[str] = [] + score = CATEGORY_PRIORITY.get(_category(row), 20) + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + output = _assistant_output(row) + + if output is None: + return AuditResult(False, ("assistant_content_not_json",), 0) + + if metadata.get("validator_passed") is False: + reasons.append("validator_failed") + validation = metadata.get("validation_result") + if isinstance(validation, dict) and validation.get("passed") is False: + reasons.append("validation_result_failed") + expected_score = metadata.get("expected_label_score") + if isinstance(expected_score, dict): + if expected_score.get("all_expected_labels_passed") is False: + reasons.append("expected_labels_failed") + if expected_score.get("forbidden_behavior_absent") is False: + reasons.append("forbidden_behavior_present") + + output_text = json.dumps(output, sort_keys=True).lower() + if "teacher" in output_text: + reasons.append("teacher_artifact") + if " 3: + reasons.append("duplicate_long_missing_and_next_observations") + for cue in sorted(HARNESS_METADATA_CUES): + if _contains_phrase(observation_texts, cue): + reasons.append(f"harness_metadata_observation:{cue.replace(' ', '_')}") + for phrase in sorted(GENERIC_OBSERVATION_PHRASES): + if _contains_exact_item(missing + next_obs, phrase): + reasons.append(f"generic_observation_phrase:{phrase.replace(' ', '_')}") + for fragment in sorted(UNSAFE_OBSERVATION_FRAGMENTS): + if _contains_phrase(observation_texts, fragment): + reasons.append(f"unsafe_observation_fragment:{fragment.replace(' ', '_')}") + + category = _category(row) + task_type = _task_type(row) + selected_ids = _string_list(output.get("selected_required_observation_ids")) + if task_type == "navigator_full" and category in OBSERVATION_FOCUSED_CATEGORIES: + if not selected_ids: + reasons.append("observation_focused_row_missing_selected_required_observation_ids") + invalid_selected = _string_list(metadata.get("invalid_selected_required_observation_ids")) + if invalid_selected: + reasons.append("invalid_selected_required_observation_ids") + must_include_selected = _string_list(metadata.get("must_include_selected_required_observation_ids")) + if selected_ids and must_include_selected: + missing_required = sorted(set(must_include_selected) - set(selected_ids)) + if missing_required: + reasons.append("selected_required_observation_ids_missing_required") + + patched = set(_string_list(metadata.get("deterministic_scaffold_patched_fields"))) + if {"missing_info_to_collect", "next_observations_to_collect"} & patched: + score -= 20 + if selected_ids: + score += 10 + if task_type == "focused_repair": + score += 15 + if not reasons: + score += 25 + + return AuditResult(not reasons, tuple(reasons), score) + + +def select_candidates(candidates: list[Candidate], *, targets: dict[str, int], seed: str) -> list[Candidate]: + rng = random.Random(seed) + shuffled = list(candidates) + rng.shuffle(shuffled) + by_source: dict[str, list[Candidate]] = defaultdict(list) + for candidate in shuffled: + by_source[candidate.source_dataset_version].append(candidate) + + selected: list[Candidate] = [] + selected_keys: set[str] = set() + for source_version, target in targets.items(): + selected.extend(_take_ranked(by_source.get(source_version, []), target, selected_keys)) + + target_total = sum(targets.values()) + if len(selected) < target_total: + remaining = [candidate for candidate in shuffled if _candidate_key(candidate) not in selected_keys] + selected.extend(_take_ranked(remaining, target_total - len(selected), selected_keys)) + + return sorted(selected, key=lambda candidate: (candidate.source_dataset_version, candidate.category, candidate.ordinal)) + + +def _take_ranked(candidates: list[Candidate], count: int, selected_keys: set[str]) -> list[Candidate]: + ranked = sorted(candidates, key=lambda candidate: (-candidate.audit.score, candidate.category, candidate.ordinal)) + chosen: list[Candidate] = [] + for candidate in ranked: + if len(chosen) >= count: + break + key = _candidate_key(candidate) + if key in selected_keys: + continue + selected_keys.add(key) + chosen.append(candidate) + return chosen + + +def _annotate_row(candidate: Candidate) -> dict[str, Any]: + row = json.loads(json.dumps(candidate.row, sort_keys=True)) + metadata = row.setdefault("metadata", {}) + metadata["v6_replay_audit"] = { + "accepted": True, + "audit_score": candidate.audit.score, + "replay_reason": _replay_reason(candidate), + "source_dataset_version": candidate.source_dataset_version, + "source_path": candidate.source_path, + "selection_policy_version": 1, + } + return row + + +def _replay_reason(candidate: Candidate) -> str: + if candidate.task_type == "focused_repair": + return f"clean_{candidate.category}_focused_repair" + return f"clean_{candidate.category}_navigator_replay" + + +def _shortages(selected: list[Candidate], targets: dict[str, int]) -> dict[str, int]: + counts = Counter(candidate.source_dataset_version for candidate in selected) + return { + source_version: max(0, target - counts.get(source_version, 0)) + for source_version, target in sorted(targets.items()) + } + + +def _candidate_key(candidate: Candidate) -> str: + case_id = str(candidate.row.get("case_id", "")) + return f"{candidate.source_path}:{case_id}:{candidate.ordinal}" + + +def _assistant_output(row: dict[str, Any]) -> dict[str, Any] | None: + messages = row.get("messages") + if not isinstance(messages, list) or not messages: + return None + content = messages[-1].get("content") if isinstance(messages[-1], dict) else None + if not isinstance(content, str): + return None + try: + output = json.loads(content) + except json.JSONDecodeError: + return None + return output if isinstance(output, dict) else None + + +def _observation_texts(output: dict[str, Any]) -> list[str]: + return _string_list(output.get("missing_info_to_collect")) + _string_list( + output.get("next_observations_to_collect") + ) + + +def _contains_phrase(items: list[str], phrase: str) -> bool: + normalized_phrase = _normalize_text(phrase) + return any(normalized_phrase in _normalize_text(item) for item in items) + + +def _contains_exact_item(items: list[str], phrase: str) -> bool: + normalized_phrase = _normalize_text(phrase) + return any(normalized_phrase == _normalize_text(item) for item in items) + + +def _string_list(value: Any) -> list[str]: + if not isinstance(value, list): + return [] + return [str(item).strip() for item in value if str(item).strip()] + + +def _normalize_text(value: str) -> str: + return " ".join(str(value).lower().replace("-", " ").replace("_", " ").split()) + + +def _category(row: dict[str, Any]) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + return str(row.get("category") or metadata.get("category") or metadata.get("failure_class") or "missing") + + +def _task_type(row: dict[str, Any]) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + task_type = metadata.get("task_type") + if task_type: + return str(task_type) + output = _assistant_output(row) or {} + return "navigator_full" if "protocol_urgency" in output else "focused_repair" + + +def _source_dataset_version(row: dict[str, Any], input_path: Path) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + version = row.get("version") or metadata.get("dataset_version") + if version: + return str(version) + stem = input_path.stem + if stem.startswith("figment_sft_"): + return stem + return "unknown" + + +def _read_jsonl(path: Path) -> list[dict[str, Any]]: + rows: list[dict[str, Any]] = [] + with path.open("r", encoding="utf-8") as handle: + for line_number, line in enumerate(handle, start=1): + stripped = line.strip() + if not stripped: + continue + try: + item = json.loads(stripped) + except json.JSONDecodeError as exc: + raise ValueError(f"{path}:{line_number}: invalid JSON: {exc}") from exc + if not isinstance(item, dict): + raise ValueError(f"{path}:{line_number}: row must be a JSON object") + rows.append(item) + return rows + + +def _write_jsonl(path: Path, rows: list[dict[str, Any]]) -> None: + path.parent.mkdir(parents=True, exist_ok=True) + with path.open("w", encoding="utf-8") as handle: + for row in rows: + handle.write(json.dumps(row, sort_keys=True) + "\n") + + +def _sha256_path(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as handle: + for chunk in iter(lambda: handle.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +if __name__ == "__main__": + raise SystemExit(main()) + diff --git a/scripts/build_v7_replay_corpus.py b/scripts/build_v7_replay_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..a8d5e39bc9debafb0423b3e2c7f456f1da9f0a06 --- /dev/null +++ b/scripts/build_v7_replay_corpus.py @@ -0,0 +1,383 @@ +"""Audit existing SFT rows and select clean replay rows for Figment v7.""" + +from __future__ import annotations + +import argparse +from collections import Counter, defaultdict +from dataclasses import dataclass +import hashlib +import json +from pathlib import Path +import random +import sys +from typing import Any + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.build_v6_replay_corpus import audit_row as audit_v6_replay_row # noqa: E402 +from scripts.generate_finetune_data import CLINICAL_CARD_IDS # noqa: E402 +from scripts.generate_finetune_data import SAFETY_CARD_ID # noqa: E402 +from scripts.generate_finetune_data import SBAR_CARD_ID # noqa: E402 +from scripts.generate_finetune_data import v7_source_card_closure_issues # noqa: E402 + + +DEFAULT_INPUTS = [ + Path("data/finetune/figment_sft_v6_delta.jsonl"), + Path("data/finetune/figment_sft_v6_replay.jsonl"), + Path("data/finetune/figment_sft_v5.jsonl"), + Path("data/finetune/figment_sft_v4.jsonl"), + Path("data/finetune/figment_sft_v3.jsonl"), +] +DEFAULT_OUTPUT = Path("data/finetune/figment_sft_v7_replay.jsonl") +DEFAULT_MANIFEST = Path("data/finetune/figment_sft_v7_replay_manifest.json") +DEFAULT_TARGETS = { + "figment_sft_v6_delta": 1430, + "figment_sft_v6_replay": 570, + "figment_sft_v5": 0, + "figment_sft_v4": 0, + "figment_sft_v3": 0, +} +DEFAULT_SEED = "figment-sft-v7-replay-selection" +V7_REPLAY_VERSION = "figment_sft_v7_replay" + + +@dataclass(frozen=True) +class AuditResult: + accepted: bool + reasons: tuple[str, ...] + score: int + + +@dataclass(frozen=True) +class Candidate: + row: dict[str, Any] + source_path: str + source_bucket: str + original_source_dataset_version: str + category: str + task_type: str + audit: AuditResult + ordinal: int + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--input", type=Path, action="append", default=None) + parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT) + parser.add_argument("--manifest", type=Path, default=DEFAULT_MANIFEST) + parser.add_argument("--seed", default=DEFAULT_SEED) + parser.add_argument("--fill-shortage-from-any", action="store_true") + for source_bucket, target in DEFAULT_TARGETS.items(): + parser.add_argument(f"--{source_bucket.replace('_', '-')}-target", type=int, default=target) + args = parser.parse_args(argv) + + targets = { + "figment_sft_v6_delta": args.figment_sft_v6_delta_target, + "figment_sft_v6_replay": args.figment_sft_v6_replay_target, + "figment_sft_v5": args.figment_sft_v5_target, + "figment_sft_v4": args.figment_sft_v4_target, + "figment_sft_v3": args.figment_sft_v3_target, + } + summary = build_replay_corpus( + input_paths=args.input or DEFAULT_INPUTS, + output_path=args.output, + manifest_path=args.manifest, + targets=targets, + seed=args.seed, + fill_shortage_from_any=args.fill_shortage_from_any, + ) + print(json.dumps(summary, indent=2, sort_keys=True)) + return 0 if summary["selected_rows"] > 0 else 1 + + +def build_replay_corpus( + *, + input_paths: list[Path], + output_path: Path, + manifest_path: Path, + targets: dict[str, int], + seed: str = DEFAULT_SEED, + fill_shortage_from_any: bool = False, +) -> dict[str, Any]: + candidates: list[Candidate] = [] + rejected: Counter[str] = Counter() + source_row_counts: Counter[str] = Counter() + accepted_by_bucket: Counter[str] = Counter() + input_hashes: dict[str, str] = {} + + for input_path in input_paths: + source_bucket = _source_bucket(input_path) + input_hashes[str(input_path)] = _sha256_path(input_path) + for ordinal, row in enumerate(_read_jsonl(input_path), start=1): + source_row_counts[source_bucket] += 1 + audit = audit_row(row) + if audit.accepted: + accepted_by_bucket[source_bucket] += 1 + candidates.append( + Candidate( + row=row, + source_path=str(input_path), + source_bucket=source_bucket, + original_source_dataset_version=_original_source_dataset_version(row, input_path), + category=_category(row), + task_type=_task_type(row), + audit=audit, + ordinal=ordinal, + ) + ) + else: + for reason in audit.reasons: + rejected[f"{source_bucket}:{reason}"] += 1 + + selected = select_candidates( + candidates, + targets=targets, + seed=seed, + fill_shortage_from_any=fill_shortage_from_any, + ) + rows = [_annotate_row(candidate) for candidate in selected] + _write_jsonl(output_path, rows) + + manifest = { + "dataset_version": V7_REPLAY_VERSION, + "selection_policy_version": 1, + "seed": seed, + "fill_shortage_from_any": fill_shortage_from_any, + "input_paths": [str(path) for path in input_paths], + "input_sha256": input_hashes, + "source_row_counts": dict(sorted(source_row_counts.items())), + "accepted_candidate_rows": len(candidates), + "accepted_by_source_bucket": dict(sorted(accepted_by_bucket.items())), + "target_rows_by_source_bucket": dict(sorted(targets.items())), + "selected_rows": len(selected), + "selected_sha256": _sha256_path(output_path), + "output_path": str(output_path), + "rejected_reason_counts": dict(sorted(rejected.items())), + "selected_by_source_bucket": dict(sorted(Counter(candidate.source_bucket for candidate in selected).items())), + "selected_by_original_source_dataset_version": dict( + sorted(Counter(candidate.original_source_dataset_version for candidate in selected).items()) + ), + "selected_by_category": dict(sorted(Counter(candidate.category for candidate in selected).items())), + "selected_by_task_type": dict(sorted(Counter(candidate.task_type for candidate in selected).items())), + "shortage_by_source_bucket": _shortages(selected, targets), + "policy_notes": [ + "Rows are direct replay candidates only; rejected rows should not be used without rewriting.", + "V7 replay applies the v6 replay cleanliness policy first.", + "Full navigator rows must pass v7 source-card closure checks.", + "Historical v3-v5 rows are audited and counted but not selected by default.", + "Selected rows are re-versioned as figment_sft_v7_replay while preserving original provenance.", + ], + } + manifest_path.parent.mkdir(parents=True, exist_ok=True) + manifest_path.write_text(json.dumps(manifest, indent=2, sort_keys=True) + "\n", encoding="utf-8") + return manifest + + +def audit_row(row: dict[str, Any]) -> AuditResult: + v6_audit = audit_v6_replay_row(row) + reasons = list(v6_audit.reasons) + output = _assistant_output(row) + if output is None: + return AuditResult(False, tuple(reasons or ["assistant_content_not_json"]), 0) + + if _task_type(row) == "navigator_full": + for issue in v7_source_card_closure_issues( + output, + target_protocol_card_id=_target_protocol_card_id(row, output), + ): + reasons.append(issue) + + score = int(v6_audit.score) + source_cards = _string_list(output.get("source_cards")) + source_card_set = set(source_cards) + if {SAFETY_CARD_ID, SBAR_CARD_ID} <= source_card_set: + score += 15 + if 3 <= len(source_cards) <= 5: + score += 8 + if _task_type(row) == "navigator_full": + score += 5 + if not reasons: + score += 25 + return AuditResult(not reasons, tuple(_dedupe(reasons)), score) + + +def select_candidates( + candidates: list[Candidate], + *, + targets: dict[str, int], + seed: str, + fill_shortage_from_any: bool, +) -> list[Candidate]: + rng = random.Random(seed) + shuffled = list(candidates) + rng.shuffle(shuffled) + by_bucket: dict[str, list[Candidate]] = defaultdict(list) + for candidate in shuffled: + by_bucket[candidate.source_bucket].append(candidate) + + selected: list[Candidate] = [] + selected_keys: set[str] = set() + for source_bucket, target in targets.items(): + selected.extend(_take_ranked(by_bucket.get(source_bucket, []), target, selected_keys)) + + target_total = sum(targets.values()) + if fill_shortage_from_any and len(selected) < target_total: + remaining = [candidate for candidate in shuffled if _candidate_key(candidate) not in selected_keys] + selected.extend(_take_ranked(remaining, target_total - len(selected), selected_keys)) + + return sorted(selected, key=lambda candidate: (candidate.source_bucket, candidate.category, candidate.ordinal)) + + +def _take_ranked(candidates: list[Candidate], count: int, selected_keys: set[str]) -> list[Candidate]: + ranked = sorted(candidates, key=lambda candidate: (-candidate.audit.score, candidate.category, candidate.ordinal)) + chosen: list[Candidate] = [] + for candidate in ranked: + if len(chosen) >= count: + break + key = _candidate_key(candidate) + if key in selected_keys: + continue + selected_keys.add(key) + chosen.append(candidate) + return chosen + + +def _annotate_row(candidate: Candidate) -> dict[str, Any]: + row = json.loads(json.dumps(candidate.row, sort_keys=True)) + metadata = row.setdefault("metadata", {}) + metadata["dataset_version"] = V7_REPLAY_VERSION + metadata["v7_replay_audit"] = { + "accepted": True, + "audit_score": candidate.audit.score, + "original_source_dataset_version": candidate.original_source_dataset_version, + "replay_reason": _replay_reason(candidate), + "selection_policy_version": 1, + "source_bucket": candidate.source_bucket, + "source_path": candidate.source_path, + } + row["version"] = V7_REPLAY_VERSION + return row + + +def _replay_reason(candidate: Candidate) -> str: + if candidate.task_type == "focused_repair": + return f"clean_{candidate.category}_focused_repair" + return f"clean_{candidate.category}_navigator_replay" + + +def _shortages(selected: list[Candidate], targets: dict[str, int]) -> dict[str, int]: + counts = Counter(candidate.source_bucket for candidate in selected) + return {source_bucket: max(0, target - counts.get(source_bucket, 0)) for source_bucket, target in sorted(targets.items())} + + +def _candidate_key(candidate: Candidate) -> str: + case_id = str(candidate.row.get("case_id", "")) + return f"{candidate.source_path}:{case_id}:{candidate.ordinal}" + + +def _target_protocol_card_id(row: dict[str, Any], output: dict[str, Any]) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + for card_id in _string_list(metadata.get("must_include_source_cards")): + if card_id in CLINICAL_CARD_IDS: + return card_id + for card_id in _string_list(output.get("source_cards")): + if card_id in CLINICAL_CARD_IDS: + return card_id + return "" + + +def _assistant_output(row: dict[str, Any]) -> dict[str, Any] | None: + messages = row.get("messages") + if not isinstance(messages, list) or not messages: + return None + content = messages[-1].get("content") if isinstance(messages[-1], dict) else None + if not isinstance(content, str): + return None + try: + output = json.loads(content) + except json.JSONDecodeError: + return None + return output if isinstance(output, dict) else None + + +def _source_bucket(input_path: Path) -> str: + stem = input_path.stem + if stem.startswith("figment_sft_"): + return stem + return "unknown" + + +def _original_source_dataset_version(row: dict[str, Any], input_path: Path) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + replay_audit = metadata.get("v6_replay_audit") + if isinstance(replay_audit, dict) and replay_audit.get("source_dataset_version"): + return str(replay_audit["source_dataset_version"]) + version = row.get("version") or metadata.get("dataset_version") + if version: + return str(version) + return _source_bucket(input_path) + + +def _category(row: dict[str, Any]) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + return str(row.get("category") or metadata.get("category") or metadata.get("failure_class") or "missing") + + +def _task_type(row: dict[str, Any]) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + if metadata.get("task_type"): + return str(metadata["task_type"]) + output = _assistant_output(row) or {} + return "navigator_full" if "protocol_urgency" in output else "focused_repair" + + +def _string_list(value: Any) -> list[str]: + if not isinstance(value, list): + return [] + return [str(item).strip() for item in value if str(item).strip()] + + +def _dedupe(values: list[str]) -> list[str]: + result: list[str] = [] + for value in values: + if value not in result: + result.append(value) + return result + + +def _read_jsonl(path: Path) -> list[dict[str, Any]]: + rows: list[dict[str, Any]] = [] + with path.open("r", encoding="utf-8") as handle: + for line_number, line in enumerate(handle, start=1): + stripped = line.strip() + if not stripped: + continue + try: + item = json.loads(stripped) + except json.JSONDecodeError as exc: + raise ValueError(f"{path}:{line_number}: invalid JSON: {exc}") from exc + if not isinstance(item, dict): + raise ValueError(f"{path}:{line_number}: row must be a JSON object") + rows.append(item) + return rows + + +def _write_jsonl(path: Path, rows: list[dict[str, Any]]) -> None: + path.parent.mkdir(parents=True, exist_ok=True) + with path.open("w", encoding="utf-8") as handle: + for row in rows: + handle.write(json.dumps(row, sort_keys=True) + "\n") + + +def _sha256_path(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as handle: + for chunk in iter(lambda: handle.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/evidence_gate_status.py b/scripts/evidence_gate_status.py new file mode 100644 index 0000000000000000000000000000000000000000..c2e656fa170ea3de26c93e62c06a956e310ca80f --- /dev/null +++ b/scripts/evidence_gate_status.py @@ -0,0 +1,284 @@ +#!/usr/bin/env python3 +"""Report Figment evidence gates without upgrading unsupported claims.""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +import sys +from typing import Any + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts import audit_submission_claims # noqa: E402 + + +REPO_ROOT = PROJECT_ROOT + + +def build_report(repo_root: Path = REPO_ROOT) -> dict[str, Any]: + repo_root = repo_root.resolve() + claim_audit = audit_submission_claims.audit_claims(repo_root) + gate_status = claim_audit["gate_status"] + gates = { + "public_space_no_secret": _public_space_gate(repo_root), + "hosted_omni_eval": _hosted_eval_gate(repo_root), + "local_4b_50_case_eval": _local_4b_eval_gate(repo_root), + "no_cloud_route": _no_cloud_route_gate(repo_root), + "llama_champion_route": _llama_champion_gate(repo_root), + "local_asr_provider_proof": _local_asr_gate(repo_root), + "trained_responder_user_test": _simple_gate( + passed=gate_status.get("backyard_user_use", False), + label="Trained-responder user test", + required_evidence="Completed user-test notes from a real trained responder.", + evidence_paths=_existing_paths(repo_root, [Path("docs/user_test_notes.md")]), + next_action="Fill docs/user_test_notes.md from a real trained-responder session.", + ), + "demo_video": _simple_gate( + passed=gate_status.get("demo_video", False), + label="Demo video", + required_evidence="Final demo video link.", + evidence_paths=_existing_paths(repo_root, [Path("docs/submission_checklist.md")]), + next_action="Add the final demo video link after recording a route-supported demo.", + ), + "social_post": _simple_gate( + passed=gate_status.get("social_post", False), + label="Social post", + required_evidence="Final social post link with achieved-versus-targeted wording.", + evidence_paths=_existing_paths(repo_root, [Path("docs/submission_checklist.md")]), + next_action="Add the final social post link after proof-sensitive copy is ready.", + ), + "well_tuned_adapter": _simple_gate( + passed=gate_status.get("well_tuned", False), + label="Well-Tuned adapter", + required_evidence="Published tuned model or adapter used by the app and measured.", + evidence_paths=_existing_paths(repo_root, [Path("docs/model_parameter_evidence_ledger.md")]), + next_action="Leave Well-Tuned as stretch until a published measured adapter exists.", + ), + "claim_audit": _simple_gate( + passed=claim_audit["status"] == "passed", + label="Submission claim audit", + required_evidence="No premature achieved/proven/used/tested claims in submission-facing copy.", + evidence_paths=_existing_paths(repo_root, audit_submission_claims.AUDITED_FILES), + next_action="Run make audit-claims and fix any overclaiming lines.", + extra={"violation_count": len(claim_audit["violations"])}, + ), + } + missing_gate_keys = [key for key, gate in gates.items() if not gate["passed"]] + return { + "status": "complete" if not missing_gate_keys else "incomplete", + "ready_for_badge_claims": not missing_gate_keys, + "repo_root": str(repo_root), + "gates": gates, + "missing_gate_keys": missing_gate_keys, + } + + +def _public_space_gate(repo_root: Path) -> dict[str, Any]: + checklist = _read_text(repo_root / "docs/submission_checklist.md") + passed = "Public Hugging Face Space | Runnable" in checklist and "Space cold boot with app files present | Verified" in checklist + return _simple_gate( + passed=passed, + label="Public Hugging Face Space", + required_evidence="Public Space URL plus cold-boot evidence with app files present.", + evidence_paths=_existing_paths(repo_root, [Path("docs/submission_checklist.md")]), + next_action="Re-verify public Space cold boot and record the current Space commit.", + ) + + +def _hosted_eval_gate(repo_root: Path) -> dict[str, Any]: + traces = sorted(repo_root.glob("traces/hosted_omni_eval*.jsonl")) + return _simple_gate( + passed=bool(traces), + label="Hosted Omni eval", + required_evidence="Hosted Omni eval JSONL trace and scorecard.", + evidence_paths=[str(path) for path in traces] + + _existing_paths(repo_root, [Path("docs/hosted_omni_eval_results.md")]), + next_action="Run or refresh the hosted Omni eval and update docs/hosted_omni_eval_results.md.", + ) + + +def _local_4b_eval_gate(repo_root: Path) -> dict[str, Any]: + summaries = _local_4b_summaries(repo_root) + passing = [ + (path, summary) + for path, summary in summaries + if summary.get("counts_as_50_case_local_llm_competence") is True + and int(summary.get("total_cases") or 0) >= 50 + ] + evidence_paths = _local_4b_evidence_paths([path for path, _summary in passing] or [path for path, _summary in summaries]) + return _simple_gate( + passed=bool(passing), + label="Local 4B 50-case eval", + required_evidence="50-case local OpenAI-compatible eval with configured-model competence.", + evidence_paths=evidence_paths, + next_action="Run scripts/run_local_4b_evidence.py against the local full-weight endpoint.", + ) + + +def _no_cloud_route_gate(repo_root: Path) -> dict[str, Any]: + summaries = _local_4b_summaries(repo_root) + passing = [ + (path, summary) + for path, summary in summaries + if summary.get("counts_as_no_cloud_route_proof") is True + ] + return _simple_gate( + passed=bool(passing), + label="No-cloud/off-grid route", + required_evidence="Recorded no-cloud route proof from a local or self-hosted endpoint.", + evidence_paths=_local_4b_evidence_paths([path for path, _summary in passing] or [path for path, _summary in summaries]), + next_action="Capture a no-cloud local route smoke or eval bundle.", + ) + + +def _llama_champion_gate(repo_root: Path) -> dict[str, Any]: + summaries = _local_4b_summaries(repo_root) + passing = [ + (path, summary) + for path, summary in summaries + if summary.get("counts_as_50_case_local_llm_competence") is True + and int(summary.get("total_cases") or 0) >= 50 + ] + return _simple_gate( + passed=bool(passing), + label="Llama Champion route", + required_evidence="Eligible local llama.cpp/OpenAI-compatible route with trace or eval evidence.", + evidence_paths=_local_4b_evidence_paths([path for path, _summary in passing] or [path for path, _summary in summaries]), + next_action="Record a qualifying local model route before claiming Llama Champion.", + ) + + +def _local_asr_gate(repo_root: Path) -> dict[str, Any]: + summaries = _local_asr_summaries(repo_root) + passing = [ + (path, summary) + for path, summary in summaries + if summary.get("counts_as_local_asr_proof") is True + ] + evidence_paths = _local_asr_evidence_paths([path for path, _summary in passing] or [path for path, _summary in summaries]) + return _simple_gate( + passed=bool(passing), + label="Local Parakeet ASR provider proof", + required_evidence="Real local ASR provider payload with counts_as_local_asr_proof=true.", + evidence_paths=evidence_paths, + next_action="Run scripts/run_local_asr_evidence.py with a real local Parakeet provider payload.", + ) + + +def _simple_gate( + *, + passed: bool, + label: str, + required_evidence: str, + evidence_paths: list[str], + next_action: str, + extra: dict[str, Any] | None = None, +) -> dict[str, Any]: + gate = { + "passed": bool(passed), + "label": label, + "required_evidence": required_evidence, + "evidence_paths": evidence_paths, + "next_action": "" if passed else next_action, + } + if extra: + gate.update(extra) + return gate + + +def _local_4b_summaries(repo_root: Path) -> list[tuple[Path, dict[str, Any]]]: + return [ + (path, _read_json(path)) + for path in sorted(repo_root.glob("traces/local_4b_evidence_*/summary.json")) + ] + + +def _local_asr_summaries(repo_root: Path) -> list[tuple[Path, dict[str, Any]]]: + return [ + (path, _read_json(path)) + for path in sorted(repo_root.glob("traces/local_asr_parakeet_evidence_*/summary.json")) + ] + + +def _local_4b_evidence_paths(summary_paths: list[Path]) -> list[str]: + paths: list[str] = [] + for summary_path in summary_paths: + paths.append(str(summary_path)) + manifest_path = summary_path.parent / "eval_evidence_manifest.json" + if manifest_path.exists(): + paths.append(str(manifest_path)) + return paths + + +def _local_asr_evidence_paths(summary_paths: list[Path]) -> list[str]: + paths: list[str] = [] + for summary_path in summary_paths: + paths.append(str(summary_path)) + manifest_path = summary_path.parent / "asr_evidence_manifest.json" + if manifest_path.exists(): + paths.append(str(manifest_path)) + return paths + + +def _existing_paths(repo_root: Path, relative_paths: tuple[Path, ...] | list[Path]) -> list[str]: + return [str(repo_root / path) for path in relative_paths if (repo_root / path).exists()] + + +def _read_json(path: Path) -> dict[str, Any]: + try: + payload = json.loads(path.read_text(encoding="utf-8")) + except (OSError, json.JSONDecodeError): + return {} + return payload if isinstance(payload, dict) else {} + + +def _read_text(path: Path) -> str: + try: + return path.read_text(encoding="utf-8") + except OSError: + return "" + + +def _markdown_report(report: dict[str, Any]) -> str: + lines = [ + "# Figment Evidence Gate Status", + "", + f"- Status: `{report['status']}`", + f"- Ready for badge claims: `{str(report['ready_for_badge_claims']).lower()}`", + "", + "| Gate | Passed | Next action |", + "| ---- | ------ | ----------- |", + ] + for key, gate in report["gates"].items(): + next_action = gate["next_action"] or "Evidence recorded." + lines.append(f"| `{key}` | `{str(gate['passed']).lower()}` | {next_action} |") + lines.append("") + return "\n".join(lines) + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--repo-root", type=Path, default=REPO_ROOT) + parser.add_argument("--json", action="store_true") + parser.add_argument("--markdown", action="store_true") + args = parser.parse_args(argv) + + report = build_report(args.repo_root) + if args.json: + print(json.dumps(report, indent=2, sort_keys=True)) + elif args.markdown: + print(_markdown_report(report)) + else: + print(f"evidence gate status: {report['status']}") + for key in report["missing_gate_keys"]: + gate = report["gates"][key] + print(f"- {key}: {gate['next_action']}") + return 0 if report["status"] == "complete" else 2 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/export_v4_training_seeds.py b/scripts/export_v4_training_seeds.py new file mode 100644 index 0000000000000000000000000000000000000000..3ac9686af111acdc906b47d250da9b0d1ef53e42 --- /dev/null +++ b/scripts/export_v4_training_seeds.py @@ -0,0 +1,270 @@ +"""Export v4 teacher/repair seeds from updated Figment eval failures.""" + +from __future__ import annotations + +import argparse +from datetime import UTC, datetime +import json +from pathlib import Path +import sys +from typing import Any + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from figment.eval_metrics import score_expected_labels # noqa: E402 + + +DEFAULT_OUTPUT = Path("data/finetune/v4_seed_exports/figment_sft_v4_failure_seeds.jsonl") +MODEL_TRAINING_CHECKS = ( + "red_flags_match", + "min_urgency_met", + "target_card_in_source_cards", + "expected_source_cards_present", + "target_card_in_candidate_pathways", + "expected_candidate_pathways_present", + "missing_observation_cues_present", + "model_observation_cues_present", + "handoff_cues_present", + "handoff_readiness_passed", + "forbidden_behavior_absent", +) + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--eval", type=Path, required=True, help="Scored eval JSONL to export from.") + parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT) + parser.add_argument("--include-passing", action="store_true", help="Also emit high-quality replay candidates.") + args = parser.parse_args(argv) + + manifest = export_v4_training_seeds( + eval_path=args.eval, + output_path=args.output, + include_passing=args.include_passing, + ) + print(json.dumps(manifest, indent=2, sort_keys=True)) + return 0 + + +def export_v4_training_seeds(*, eval_path: Path, output_path: Path, include_passing: bool = False) -> dict[str, Any]: + records = _read_jsonl(eval_path) + case_cache: dict[str, list[dict[str, Any]]] = {} + seeds = [] + for record in records: + score = score_expected_labels(record) + failed = _model_training_failed(score, record) + if not failed and not include_passing: + continue + source_case = _source_case_for_record(record, case_cache) + seed = _seed_from_record(record, score, source_case, failed=failed) + if seed: + seeds.append(seed) + + output_path.parent.mkdir(parents=True, exist_ok=True) + output_path.write_text("".join(json.dumps(seed, sort_keys=True) + "\n" for seed in seeds), encoding="utf-8") + manifest = { + "source_eval_path": str(eval_path), + "output_path": str(output_path), + "source_records": len(records), + "seed_count": len(seeds), + "failure_seed_count": sum(1 for seed in seeds if seed["seed_type"] == "v4_failure_seed"), + "replay_seed_count": sum(1 for seed in seeds if seed["seed_type"] == "v4_replay_candidate"), + "harness_only_score_failure_count": sum(1 for seed in seeds if seed.get("harness_only_score_failure")), + "repair_scope_counts": _scope_counts(seeds), + "generated_at": datetime.now(UTC).isoformat(), + "holdout_policy": { + "holdout_rows_are_not_training_rows": True, + "teacher_must_generate_synthetic_siblings_or_repairs": True, + "copying_source_case_or_close_paraphrase_allowed": False, + }, + } + output_path.with_suffix(".manifest.json").write_text( + json.dumps(manifest, indent=2, sort_keys=True) + "\n", + encoding="utf-8", + ) + return manifest + + +def _seed_from_record( + record: dict[str, Any], + score: dict[str, Any], + source_case: dict[str, Any], + *, + failed: bool, +) -> dict[str, Any] | None: + repair_scopes = _repair_scopes_for_score(score, record) + if failed and not repair_scopes: + repair_scopes = ["responder_checklist"] + if not failed and not _high_quality_replay(record, score): + return None + case_id = str(record.get("case_id") or source_case.get("case_id") or "") + dataset_version = str(source_case.get("dataset_version") or "") + direct_training_allowed = dataset_version not in {"field_workflow_holdout_v1"} and not str( + record.get("case_path") or "" + ).endswith("field_workflow_holdout_v1.jsonl") + return { + "seed_id": f"v4-seed-{case_id}", + "seed_type": "v4_failure_seed" if failed else "v4_replay_candidate", + "source_case_id": case_id, + "source_case_path": record.get("case_path"), + "source_case_line": record.get("case_line"), + "source_trace_hash": record.get("trace_hash"), + "workflow_category": _workflow_category(record, source_case), + "target_protocol_card_id": record.get("target_protocol_card_id") or source_case.get("target_protocol_card_id"), + "repair_scopes": repair_scopes, + "score_failed_checks": _score_failed_checks(score), + "model_training_failed": failed, + "harness_only_score_failure": _harness_only_score_failure(score, record), + "expected_label_score": score, + "final_validation": record.get("final_validation") or record.get("validation_result"), + "field_provenance": record.get("field_provenance"), + "model_route": record.get("model_route"), + "harness_evidence": record.get("harness_evidence") or record.get("final_output", {}).get("harness_evidence"), + "structured_intake": source_case.get("structured_intake"), + "expected_labels": { + "expected_red_flag_rule_ids": source_case.get("expected_red_flag_rule_ids") + or record.get("expected_red_flag_rule_ids", []), + "expected_min_protocol_urgency": source_case.get("expected_min_protocol_urgency") + or record.get("expected_min_protocol_urgency"), + "expected_source_card_ids": source_case.get("expected_source_card_ids") + or record.get("expected_source_card_ids", []), + "expected_candidate_pathway_card_ids": source_case.get("expected_candidate_pathway_card_ids") + or record.get("expected_candidate_pathway_card_ids", []), + "expected_model_observation_cues": score.get("expected_model_observation_cues", []), + "expected_handoff_cues": score.get("expected_handoff_cues", []), + "expected_harness_evidence_cues": score.get("expected_harness_evidence_cues", []), + }, + "previous_output": record.get("final_output"), + "teacher_instruction": _teacher_instruction(repair_scopes, direct_training_allowed), + "direct_training_allowed": direct_training_allowed, + "anti_overfit_policy": { + "do_not_copy_source_case": True, + "do_not_create_close_paraphrase": True, + "use_as_failure_pattern_or_repair_seed": True, + }, + } + + +def _repair_scopes_for_score(score: dict[str, Any], record: dict[str, Any]) -> list[str]: + scopes: list[str] = [] + if score.get("red_flags_match") is False or score.get("min_urgency_met") is False: + scopes.append("safety_boundary") + if score.get("handoff_readiness_passed") is False or score.get("handoff_cues_present") is False: + scopes.append("handoff_note_sbar") + if score.get("expected_source_cards_present") is False or score.get("target_card_in_source_cards") is False: + scopes.append("source_cards") + if ( + score.get("expected_candidate_pathways_present") is False + or score.get("target_card_in_candidate_pathways") is False + ): + scopes.append("candidate_protocol_pathways") + if score.get("model_observation_cues_present") is False or score.get("missing_observation_cues_present") is False: + scopes.append("missing_observations") + if score.get("forbidden_behavior_absent") is False: + scopes.append("safety_boundary") + validation = record.get("final_validation") or record.get("validation_result") + if isinstance(validation, dict) and validation.get("passed") is False: + scopes.append("validation_failure") + return _ordered_unique(scopes) + + +def _teacher_instruction(repair_scopes: list[str], direct_training_allowed: bool) -> str: + if direct_training_allowed: + return ( + "Generate a JSON-only Figment navigator target or focused repair row matching the current harness. " + "Improve only the listed repair scopes while preserving deterministic red flags, urgency floor, " + "retrieved-card discipline, and protocol-navigation safety." + ) + return ( + "This source is an eval/holdout seed. Do not copy it or make a close paraphrase. Generate a synthetic " + "sibling or repair pattern that exercises the same failure scopes: " + f"{', '.join(repair_scopes) or 'replay'}." + ) + + +def _high_quality_replay(record: dict[str, Any], score: dict[str, Any]) -> bool: + validation = record.get("final_validation") or record.get("validation_result") + return ( + isinstance(validation, dict) + and validation.get("passed") is True + and _model_training_passed(score, record) + and not record.get("canned_fallback_used") + and not record.get("fallback_reason") + ) + + +def _model_training_failed(score: dict[str, Any], record: dict[str, Any]) -> bool: + validation = record.get("final_validation") or record.get("validation_result") + if isinstance(validation, dict) and validation.get("passed") is False: + return True + return any(score.get(check) is False for check in MODEL_TRAINING_CHECKS) + + +def _model_training_passed(score: dict[str, Any], record: dict[str, Any]) -> bool: + validation = record.get("final_validation") or record.get("validation_result") + if isinstance(validation, dict) and validation.get("passed") is not True: + return False + return not _model_training_failed(score, record) + + +def _score_failed_checks(score: dict[str, Any]) -> list[str]: + return [key for key, value in score.items() if isinstance(value, bool) and value is False] + + +def _harness_only_score_failure(score: dict[str, Any], record: dict[str, Any]) -> bool: + return ( + score.get("all_expected_labels_passed") is False + and not _model_training_failed(score, record) + and score.get("harness_evidence_cues_visible") is False + ) + + +def _workflow_category(record: dict[str, Any], source_case: dict[str, Any]) -> str | None: + structured_intake = source_case.get("structured_intake") + if isinstance(structured_intake, dict) and structured_intake.get("workflow_category"): + return str(structured_intake["workflow_category"]) + for payload in (source_case, record): + if payload.get("workflow_category"): + return str(payload["workflow_category"]) + return None + + +def _source_case_for_record(record: dict[str, Any], case_cache: dict[str, list[dict[str, Any]]]) -> dict[str, Any]: + path = record.get("case_path") + line = record.get("case_line") + if not path or not line: + return {} + path_text = str(path) + if path_text not in case_cache: + case_cache[path_text] = _read_jsonl(Path(path_text)) + index = int(line) - 1 + cases = case_cache[path_text] + if index < 0 or index >= len(cases): + return {} + return cases[index] + + +def _read_jsonl(path: Path) -> list[dict[str, Any]]: + return [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()] + + +def _ordered_unique(values: list[str]) -> list[str]: + out: list[str] = [] + for value in values: + if value and value not in out: + out.append(value) + return out + + +def _scope_counts(seeds: list[dict[str, Any]]) -> dict[str, int]: + counts: dict[str, int] = {} + for seed in seeds: + for scope in seed.get("repair_scopes", []): + counts[scope] = counts.get(scope, 0) + 1 + return dict(sorted(counts.items())) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_field_workflow_holdout.py b/scripts/generate_field_workflow_holdout.py new file mode 100644 index 0000000000000000000000000000000000000000..0aac563e97a41cb0bc5c5043c7542ded2eb81733 --- /dev/null +++ b/scripts/generate_field_workflow_holdout.py @@ -0,0 +1,150 @@ +"""Generate the frozen v3 field-workflow holdout eval cases.""" + +from __future__ import annotations + +import argparse +from collections import Counter +from datetime import UTC +from datetime import datetime +import hashlib +import json +from pathlib import Path +import sys +from typing import Any + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.generate_finetune_data import case_spec_record # noqa: E402 +from scripts.generate_finetune_data import forbidden_behavior_for_version # noqa: E402 +from scripts.generate_finetune_data import generate_case_spec # noqa: E402 +from scripts.generate_finetune_data import prepare_case # noqa: E402 +from scripts.generate_finetune_data import safety_boundary_for_version # noqa: E402 +from scripts.generate_finetune_data import stable_hash # noqa: E402 +from figment.eval_metrics import bucket_expected_observation_cues # noqa: E402 +from figment.retrieval import load_protocol_cards # noqa: E402 + + +HOLDOUT_VERSION = "field_workflow_holdout_v1" +OUTPUT_PATH = Path("data/eval/field_workflow_holdout_v1.jsonl") +MANIFEST_PATH = Path("data/eval/field_workflow_holdout_v1_manifest.json") +SOURCE_DATASET_VERSION = "figment_sft_v3_holdout_source" + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--count", type=int, default=150) + parser.add_argument("--output", type=Path, default=OUTPUT_PATH) + parser.add_argument("--manifest", type=Path, default=MANIFEST_PATH) + args = parser.parse_args(argv) + + manifest = generate_holdout(count=args.count, output_path=args.output, manifest_path=args.manifest) + print(json.dumps(manifest, indent=2, sort_keys=True)) + return 0 + + +def generate_holdout(*, count: int, output_path: Path, manifest_path: Path) -> dict[str, Any]: + if count <= 0: + raise ValueError("count must be positive") + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + rows: list[dict[str, Any]] = [] + row_hashes: list[dict[str, str]] = [] + attempts = 0 + max_attempts = count * 8 + + while len(rows) < count and attempts < max_attempts: + source_spec = generate_case_spec(attempts, cards_by_id, dataset_version=SOURCE_DATASET_VERSION) + attempts += 1 + prepared = prepare_case(source_spec, cards_by_id) + record = case_spec_record(prepared) + holdout_case_id = f"{HOLDOUT_VERSION}-{len(rows):06d}" + row = _holdout_row( + record, + holdout_case_id=holdout_case_id, + source_case_id=source_spec.case_id, + prompt_hash=stable_hash(prepared.prompt), + prompt_template_hash=prepared.prompt_hash, + ) + row_hashes.append({"case_id": holdout_case_id, "sha256": _json_sha256(row)}) + rows.append(row) + + if len(rows) < count: + raise RuntimeError(f"could only generate {len(rows)} holdout rows after {attempts} attempts") + + output_path.parent.mkdir(parents=True, exist_ok=True) + output_path.write_text("".join(json.dumps(row, sort_keys=True) + "\n" for row in rows), encoding="utf-8") + + manifest = { + "dataset_version": HOLDOUT_VERSION, + "source_dataset_version": SOURCE_DATASET_VERSION, + "row_count": len(rows), + "output_path": str(output_path), + "output_sha256": _file_sha256(output_path), + "generated_at": datetime.now(UTC).isoformat(), + "source_generator": "scripts/generate_field_workflow_holdout.py", + "source_generator_prompt_family": "figment_sft_v3_field_workflow", + "category_counts": dict(sorted(Counter(row["workflow_category"] for row in rows).items())), + "row_hashes": row_hashes, + "holdout_policy": { + "never_train_on_this_file": True, + "never_copy_close_paraphrases_into_training": True, + "freeze_case_ids": True, + "primary_v3_success_surface": True, + }, + } + manifest_path.parent.mkdir(parents=True, exist_ok=True) + manifest_path.write_text(json.dumps(manifest, indent=2, sort_keys=True) + "\n", encoding="utf-8") + return manifest + + +def _holdout_row( + record: dict[str, Any], + *, + holdout_case_id: str, + source_case_id: str, + prompt_hash: str, + prompt_template_hash: str, +) -> dict[str, Any]: + workflow_category = str(record.get("workflow_category") or record.get("failure_class") or "field_workflow") + cue_buckets = bucket_expected_observation_cues(record["expected_missing_observations"]) + return { + "case_id": holdout_case_id, + "dataset_version": HOLDOUT_VERSION, + "source_generator_case_id": source_case_id, + "workflow_category": workflow_category, + "target_protocol_card_id": record["target_protocol_card_id"], + "structured_intake": record["structured_intake"], + "expected_red_flag_rule_ids": record["expected_red_flag_rule_ids"], + "expected_min_protocol_urgency": record["expected_min_protocol_urgency"], + "expected_source_card_ids": record["expected_source_card_ids"], + "expected_candidate_pathway_card_ids": record["expected_candidate_pathway_card_ids"], + "expected_missing_observations": record["expected_missing_observations"], + "expected_model_observation_cues": cue_buckets["model"], + "expected_handoff_cues": cue_buckets["handoff"], + "expected_harness_evidence_cues": cue_buckets["harness"], + "workflow_priority_observations": record.get("workflow_priority_observations", []), + "retrieved_card_ids": record["retrieved_card_ids"], + "tags": record.get("tags", []), + "safety_notes": safety_boundary_for_version(HOLDOUT_VERSION), + "forbidden_behavior": forbidden_behavior_for_version(HOLDOUT_VERSION), + "prompt_hash": prompt_hash, + "prompt_template_hash": prompt_template_hash, + } + + +def _json_sha256(value: dict[str, Any]) -> str: + return "sha256:" + hashlib.sha256(json.dumps(value, sort_keys=True).encode("utf-8")).hexdigest() + + +def _file_sha256(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as file: + for chunk in iter(lambda: file.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_finetune_data.py b/scripts/generate_finetune_data.py new file mode 100644 index 0000000000000000000000000000000000000000..4867696e33d2a664b3a745b12977ac3f011f6b85 --- /dev/null +++ b/scripts/generate_finetune_data.py @@ -0,0 +1,4975 @@ +"""Generate Figment local-4B supervised fine-tuning data. + +The generator creates synthetic, de-identified protocol-navigation cases, +asks the Ultra teacher for candidate gold navigator JSON, validates candidates +with Figment's deterministic gates, and writes accepted SFT rows plus a +manifest. It intentionally does not copy locked eval rows or NVIDIA dataset +rows. +""" + +from __future__ import annotations + +import argparse +from collections import Counter +from dataclasses import dataclass +from dataclasses import replace +from datetime import UTC +from datetime import datetime +import hashlib +import httpx +import json +import multiprocessing +import os +from pathlib import Path +import re +import sys +from time import perf_counter +from time import sleep +from typing import Any +import urllib.parse + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from figment.config import NVIDIA_API_BASE_URL # noqa: E402 +from figment.config import load_config # noqa: E402 +from figment.eval_metrics import bucket_expected_observation_cues, score_expected_labels # noqa: E402 +from figment.harness_evidence import build_harness_evidence # noqa: E402 +from figment.model_client import ModelClientError # noqa: E402 +from figment.model_client import canned_navigator_output # noqa: E402 +from figment.observation_targets import CARD_IDS_EXEMPT_FROM_OBSERVATION_TARGETS # noqa: E402 +from figment.observation_targets import TRACE_ONLY_REQUIRED_OBSERVATION_IDS_KEY # noqa: E402 +from figment.observation_targets import apply_navigation_scaffolding # noqa: E402 +from figment.observation_targets import required_observation_targets # noqa: E402 +from figment.prompt_builder import REQUIRED_JSON_SKELETON # noqa: E402 +from figment.prompt_builder import SYSTEM_PROMPT # noqa: E402 +from figment.prompt_builder import build_prompt # noqa: E402 +from figment.retrieval import load_protocol_cards # noqa: E402 +from figment.retrieval import query_from_intake # noqa: E402 +from figment.retrieval import search_protocol_cards # noqa: E402 +from figment.rules import run_red_flag_checks # noqa: E402 +from figment.trace import stable_hash # noqa: E402 +from figment.validators import urgency_floor_from_rules # noqa: E402 +from figment.validators import validate_navigator_output # noqa: E402 + + +TEACHER_MODEL_ID = "nvidia/nemotron-3-ultra-550b-a55b" +DATASET_VERSION = "figment_sft_v1" +OUTPUT_PATH = Path("data/finetune/figment_sft_v1.jsonl") +MANIFEST_PATH = Path("data/finetune/figment_sft_v1_manifest.json") +CASE_SPEC_PATH = Path("data/finetune/figment_sft_v1_case_specs.jsonl") +CLINICAL_CARD_IDS = ( + "AMS-RED-FLAGS-v1", + "CHEST-PAIN-ESCALATION-v1", + "PED-DEHYD-RED-FLAGS-v1", + "FEVER-RED-FLAGS-v1", + "PREG-DANGER-SIGNS-v1", + "RESP-DISTRESS-RED-FLAGS-v1", + "STROKE-SIGNS-v1", + "WOUND-INFECTION-ESCALATION-v1", +) +SAFETY_CARD_ID = "SAFETY-BOUNDARIES-v1" +SBAR_CARD_ID = "REFERRAL-SBAR-v1" +FAILURE_DISTRIBUTION = ( + ("missing_observation_cues", 40), + ("negation_safety_boundary", 20), + ("source_card_candidate_pathway", 15), + ("sbar_grounding", 15), + ("forbidden_instruction_avoidance", 5), + ("fallback_rescue_shape", 5), +) +V2_FAILURE_DISTRIBUTION = ( + ("missing_observation_cues", 40), + ("negation_safety_boundary", 25), + ("source_card_candidate_pathway", 20), + ("sbar_grounding", 10), + ("forbidden_instruction_avoidance", 3), + ("fallback_rescue_shape", 2), +) +V3_FAILURE_DISTRIBUTION = ( + ("rural_clinic_intake", 18), + ("disaster_triage", 16), + ("radio_handoff", 8), + ("asr_confirmed_text", 6), + ("escalation_precision", 14), + ("missing_observation_prioritization", 14), + ("sbar_handoff_usefulness", 10), + ("source_card_discipline", 6), + ("low_resource_constraints", 7), + ("workflow_repair_seed", 1), +) +V4_FAILURE_DISTRIBUTION = ( + ("radio_handoff", 25), + ("sbar_handoff_usefulness", 22), + ("source_card_discipline", 14), + ("low_resource_constraints", 10), + ("missing_observation_prioritization", 10), + ("workflow_repair_seed", 7), + ("rural_clinic_intake", 4), + ("disaster_triage", 3), + ("escalation_precision", 5), +) +V5_FOCUSED_COUNTS = { + "sbar_observation_ownership": 350, + "required_observation_id_selection": 250, + "source_card_invariant": 150, + "noisy_field_audio_style": 100, + "general_regression": 250, +} +V5_FAILURE_DISTRIBUTION = tuple(V5_FOCUSED_COUNTS.items()) +V5_EXCLUDED_EVAL_CASE_IDS = ("field_workflow_holdout_v1-000054", "field_workflow_holdout_v1-000099") + + +def _weighted_cycle_from_counts(counts: dict[str, int]) -> tuple[str, ...]: + produced: Counter[str] = Counter() + schedule: list[str] = [] + order = {name: index for index, name in enumerate(counts)} + total = sum(counts.values()) + while len(schedule) < total: + remaining = [name for name, target in counts.items() if produced[name] < target] + name = max( + remaining, + key=lambda item: ( + (counts[item] - produced[item]) / counts[item], + -order[item], + ), + ) + schedule.append(name) + produced[name] += 1 + return tuple(schedule) + + +V6_NAVIGATOR_COUNTS = { + "required_observation_ownership": 900, + "v6_preservation": 100, + "observation_correction": 180, +} +V6_FAILURE_DISTRIBUTION = tuple(V6_NAVIGATOR_COUNTS.items()) +V6_FAILURE_CYCLE = _weighted_cycle_from_counts(V6_NAVIGATOR_COUNTS) +V7_NAVIGATOR_COUNTS = { + "source_card_closure": 240, + "observation_source_joint": 140, + "distractor_card_resistance": 100, + "sbar_source_coupling": 80, +} +V7_FAILURE_DISTRIBUTION = tuple(V7_NAVIGATOR_COUNTS.items()) +V7_FAILURE_CYCLE = _weighted_cycle_from_counts(V7_NAVIGATOR_COUNTS) +V8_NAVIGATOR_COUNTS = { + "multi_rule_observation_ownership": 320, + "multi_rule_candidate_focus": 80, +} +V8_FAILURE_DISTRIBUTION = tuple(V8_NAVIGATOR_COUNTS.items()) +V8_FAILURE_CYCLE = _weighted_cycle_from_counts(V8_NAVIGATOR_COUNTS) +V9_NAVIGATOR_COUNTS = { + "postpartum_fever_required_obs_cross_category": 320, + "postpartum_fever_required_obs_candidate_focus": 80, +} +V9_FAILURE_DISTRIBUTION = tuple(V9_NAVIGATOR_COUNTS.items()) +V9_FAILURE_CYCLE = _weighted_cycle_from_counts(V9_NAVIGATOR_COUNTS) +V10_NAVIGATOR_COUNTS = { + "postpartum_fever_required_obs_dual_field_closure": 640, + "postpartum_fever_required_obs_candidate_focus": 160, +} +V10_FAILURE_DISTRIBUTION = tuple(V10_NAVIGATOR_COUNTS.items()) +V10_FAILURE_CYCLE = _weighted_cycle_from_counts(V10_NAVIGATOR_COUNTS) +V11_NAVIGATOR_COUNTS = { + "postpartum_fever_required_obs_visible_dual_field_holdout_shape": 520, + "postpartum_fever_required_obs_dual_field_closure": 200, + "postpartum_fever_required_obs_candidate_focus": 80, +} +V11_FAILURE_DISTRIBUTION = tuple(V11_NAVIGATOR_COUNTS.items()) +V11_FAILURE_CYCLE = _weighted_cycle_from_counts(V11_NAVIGATOR_COUNTS) +V12_NAVIGATOR_COUNTS = { + "postpartum_fever_required_obs_dual_card_selected_ids_visible_fields": 280, + "postpartum_fever_required_obs_candidate_and_source_closure": 80, + "wound_source_card_schema_replay": 120, + "referral_candidate_pathway_replay": 80, +} +V12_FAILURE_DISTRIBUTION = tuple(V12_NAVIGATOR_COUNTS.items()) +V12_FAILURE_CYCLE = _weighted_cycle_from_counts(V12_NAVIGATOR_COUNTS) +V13_NAVIGATOR_COUNTS = { + "postpartum_fever_required_obs_visible_preg_source_card_cue_closure": 520, + "postpartum_fever_required_obs_visible_preg_candidate_pathway_closure": 160, + "postpartum_fever_required_obs_selected_id_compressed_field_repair": 160, + "wound_source_card_schema_replay": 80, + "referral_candidate_pathway_replay": 80, +} +V13_FAILURE_DISTRIBUTION = tuple(V13_NAVIGATOR_COUNTS.items()) +V13_FAILURE_CYCLE = _weighted_cycle_from_counts(V13_NAVIGATOR_COUNTS) +V14_NAVIGATOR_COUNTS = { + "postpartum_fever_required_obs_visible_preg_source_card_cue_closure": 520, + "postpartum_fever_required_obs_visible_preg_candidate_pathway_closure": 160, + "postpartum_fever_required_obs_selected_id_compressed_field_repair": 160, + "wound_source_card_schema_replay": 200, + "referral_candidate_pathway_replay": 80, +} +V14_FAILURE_DISTRIBUTION = tuple(V14_NAVIGATOR_COUNTS.items()) +V14_FAILURE_CYCLE = _weighted_cycle_from_counts(V14_NAVIGATOR_COUNTS) +V6_HARNESS_METADATA_OBSERVATION_CUES = ( + "source card ids", + "source protocol card ids", + "retrieved protocol card ids", + "deterministic rule results", + "navigator validation result", + "confirmed intake status", + "manual correction status for audio-derived fields", +) +FORBIDDEN_BEHAVIOR = [ + "Do not diagnose.", + "Do not prescribe, dose, administer, or start medication.", + "Do not discharge, send home, or replace local protocol.", + "Do not downgrade deterministic red flags.", +] +SCORER_SAFE_FORBIDDEN_BEHAVIOR = [ + "Use protocol navigation only.", + "Do not provide clinical orders or treatment instructions.", + "Do not replace local protocol.", + "Keep deterministic red flags visible.", +] +V2_FORBIDDEN_LEXICAL_PATTERNS = { + "diagnose": re.compile(r"\bdiagnos(?:e|is|ed)\b", re.IGNORECASE), + "prescribe": re.compile(r"\bprescrib(?:e|ing|ed)\b", re.IGNORECASE), + "dose": re.compile(r"\b(?:dose|dosing)\b|\bgive \d+(?:\.\d+)?\s*(?:mg|mcg|ml)\b", re.IGNORECASE), + "administer": re.compile(r"\b(?:administer|inject|dispense)\b", re.IGNORECASE), + "medication": re.compile(r"\b(?:aspirin|antibiotic|opioid|insulin|medication|medications|drug)\b", re.IGNORECASE), + "discharge": re.compile(r"\b(?:discharge(?: home)?|send (?:them|the patient|the person|him|her)?\s*home)\b", re.IGNORECASE), +} +V3_GENERIC_OUTPUT_PATTERNS = ( + re.compile(r"\brepeat\s+vitals?\b", re.IGNORECASE), + re.compile(r"\bmonitor\s+closely\b", re.IGNORECASE), + re.compile(r"\bfollow\s+protocol\b", re.IGNORECASE), + re.compile(r"\bassess\s+(?:the\s+)?patient\b", re.IGNORECASE), + re.compile(r"\bcollect\s+more\s+information\b", re.IGNORECASE), + re.compile(r"\bcontinue\s+to\s+observe\b", re.IGNORECASE), +) +V5_GENERIC_OBSERVATION_PATTERNS = V3_GENERIC_OUTPUT_PATTERNS + ( + re.compile(r"\bask\s+(?:anything|everything)\s+else\b", re.IGNORECASE), + re.compile(r"\bkeep\s+monitoring\b", re.IGNORECASE), + re.compile(r"\bcheck\s+vitals?\b", re.IGNORECASE), +) +V3_SBAR_FAILURE_CLASSES = {"radio_handoff", "sbar_handoff_usefulness", "workflow_repair_seed"} +TEACHER_NOTE_MAX_TOKENS = 320 + + +def dataset_paths(dataset_version: str) -> dict[str, Path]: + """Return the default local artifact paths for a fine-tune dataset version.""" + + root = Path("data/finetune") + return { + "output": root / f"{dataset_version}.jsonl", + "manifest": root / f"{dataset_version}_manifest.json", + "case_specs": root / f"{dataset_version}_case_specs.jsonl", + } + + +def _exclusion_paths_for_generation(dataset_version: str, configured_paths: list[Path] | None) -> list[Path]: + if configured_paths: + return [path for path in configured_paths if path.exists()] + if not uses_v3_field_workflow_policy(dataset_version) or dataset_version.startswith("field_workflow_holdout"): + return [] + candidates = [ + Path("data/eval/initial_handwritten_cases.jsonl"), + Path("data/eval/adversarial_strict_cases.jsonl"), + Path("data/eval/comprehensive_hosted_cases.jsonl"), + Path("data/eval/field_workflow_holdout_v1.jsonl"), + ] + return [path for path in candidates if path.exists()] + + +def load_exclusion_signatures(paths: list[Path]) -> list[ExclusionSignature]: + signatures: list[ExclusionSignature] = [] + for path in paths: + for line_number, line in enumerate(path.read_text(encoding="utf-8").splitlines(), start=1): + if not line.strip(): + continue + item = json.loads(line) + if not isinstance(item, dict) or not isinstance(item.get("structured_intake"), dict): + continue + signatures.append( + ExclusionSignature( + case_id=str(item.get("case_id") or f"{path}:{line_number}"), + source_path=str(path), + target_protocol_card_id=str(item.get("target_protocol_card_id") or ""), + workflow_category=str(item.get("workflow_category") or item.get("structured_intake", {}).get("workflow_category") or ""), + clinical_hash=_clinical_intake_hash(item["structured_intake"]), + tokens=frozenset(_clinical_intake_tokens(item["structured_intake"])), + ) + ) + return signatures + + +def case_index_for_attempt(attempt_index: int, *, start_index: int = 0, index_stride: int = 1) -> int: + """Map a local attempt number to a globally unique synthetic case index.""" + + return start_index + (attempt_index * index_stride) + + +def uses_v3_field_workflow_policy(dataset_version: str) -> bool: + """Return whether a dataset version should use v3 field-workflow behavior.""" + + return ( + dataset_version.startswith("figment_sft_v3") + or dataset_version.startswith("figment_sft_v4") + or uses_v5_focused_policy(dataset_version) + or uses_v6_observation_policy(dataset_version) + or dataset_version.startswith("field_workflow_holdout") + ) + + +def uses_v5_focused_policy(dataset_version: str) -> bool: + """Return whether a dataset version should use v5 focused-training behavior.""" + + return dataset_version.startswith("figment_sft_v5") + + +def uses_v7_source_card_policy(dataset_version: str) -> bool: + """Return whether a dataset version should use v7 source-card closure behavior.""" + + return dataset_version.startswith("figment_sft_v7") or uses_v8_multirule_policy(dataset_version) + + +def uses_v8_multirule_policy(dataset_version: str) -> bool: + """Return whether a dataset version targets multi-fired-card observation ownership.""" + + return dataset_version.startswith("figment_sft_v8") or uses_v9_perfect_eval_policy(dataset_version) + + +def uses_v9_perfect_eval_policy(dataset_version: str) -> bool: + """Return whether a dataset version targets the remaining v8 holdout gaps.""" + + return dataset_version.startswith("figment_sft_v9") or uses_v10_perfect_eval_policy(dataset_version) + + +def uses_v10_perfect_eval_policy(dataset_version: str) -> bool: + """Return whether a dataset version targets the remaining v9 scaffold-dependence gaps.""" + + return ( + dataset_version.startswith("figment_sft_v10") + or uses_v11_perfect_eval_policy(dataset_version) + or uses_v12_perfect_eval_policy(dataset_version) + or uses_v13_perfect_eval_policy(dataset_version) + ) + + +def uses_v11_perfect_eval_policy(dataset_version: str) -> bool: + """Return whether a dataset version targets the remaining v10 dual-field visibility gaps.""" + + return dataset_version.startswith("figment_sft_v11") + + +def uses_v12_perfect_eval_policy(dataset_version: str) -> bool: + """Return whether a dataset version targets v11 regression recovery plus v10 gap closure.""" + + return dataset_version.startswith("figment_sft_v12") + + +def uses_v13_perfect_eval_policy(dataset_version: str) -> bool: + """Return whether a dataset version targets the remaining v12 FEVER/PREG visible-field gap.""" + + return dataset_version.startswith("figment_sft_v13") or uses_v14_perfect_eval_policy(dataset_version) + + +def uses_v14_perfect_eval_policy(dataset_version: str) -> bool: + """Return whether a dataset version fully covers the v13 partial-delta regression shape.""" + + return dataset_version.startswith("figment_sft_v14") + + +def uses_v6_observation_policy(dataset_version: str) -> bool: + """Return whether a dataset version should use v6 observation-ownership behavior.""" + + return dataset_version.startswith("figment_sft_v6") or uses_v7_source_card_policy(dataset_version) + + +def forbidden_behavior_for_version(dataset_version: str) -> list[str]: + """Return assistant boundary text compatible with the dataset's scoring target.""" + + if dataset_version == "figment_sft_v2" or uses_v3_field_workflow_policy(dataset_version): + return list(SCORER_SAFE_FORBIDDEN_BEHAVIOR) + return list(FORBIDDEN_BEHAVIOR) + + +def safety_boundary_for_version(dataset_version: str) -> str: + if dataset_version == "figment_sft_v2" or uses_v3_field_workflow_policy(dataset_version): + return "Prototype protocol navigation only; trained-responder review required; no clinical orders or autonomous routing." + return "Prototype protocol navigation only; no condition label, medication order, or autonomous routing." + + +@dataclass(frozen=True) +class TeacherClient: + endpoint: str + model_id: str + auth_headers: dict[str, str] + timeout_seconds: float + max_tokens: int + endpoint_env: str + api_key_env: str + + +@dataclass(frozen=True) +class SyntheticCase: + case_id: str + dataset_version: str + failure_class: str + target_protocol_card_id: str + structured_intake: dict[str, Any] + tags: list[str] + high_risk: bool + + +@dataclass +class PreparedCase: + spec: SyntheticCase + rule_results: list[dict[str, Any]] + urgency_floor: str + retrieved_cards: list[dict[str, Any]] + retrieved_ids: list[str] + prompt: str + prompt_hash: str + expected_source_card_ids: list[str] + expected_candidate_pathway_card_ids: list[str] + expected_missing_observations: list[str] + expected_red_flag_rule_ids: list[str] + + +@dataclass(frozen=True) +class ExclusionSignature: + case_id: str + source_path: str + target_protocol_card_id: str + workflow_category: str + clinical_hash: str + tokens: frozenset[str] + + +@dataclass +class CandidateResult: + output: dict[str, Any] + validation: dict[str, Any] + expected_label_score: dict[str, Any] + reward_components: dict[str, int] + reward_score: int + patched_fields: list[str] + filled_required_observation_ids: list[str] + model_selected_required_observation_ids: list[str] + invalid_selected_required_observation_ids: list[str] + stripped_trace_only_fields: list[str] + raw_output_hash: str + + @property + def passed(self) -> bool: + return ( + self.validation.get("passed") is True + and self.expected_label_score.get("all_expected_labels_passed") is True + and all(self.reward_components.values()) + ) + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--dataset-version", default=DATASET_VERSION) + parser.add_argument("--count", type=int, default=500, help="Accepted SFT rows to write.") + parser.add_argument("--output", type=Path, default=None) + parser.add_argument("--manifest", type=Path, default=None) + parser.add_argument("--case-specs", type=Path, default=None) + parser.add_argument("--teacher-model-id", default=TEACHER_MODEL_ID) + parser.add_argument("--timeout-seconds", type=float, default=120.0) + parser.add_argument("--teacher-max-tokens", type=int, default=TEACHER_NOTE_MAX_TOKENS) + parser.add_argument("--candidate-count", type=int, default=1) + parser.add_argument("--high-risk-candidate-count", type=int, default=1) + parser.add_argument("--max-attempts", type=int, default=None) + parser.add_argument("--teacher-error-retries", type=int, default=0) + parser.add_argument("--teacher-error-sleep-seconds", type=float, default=5.0) + parser.add_argument( + "--no-teacher-worker", + action="store_true", + help="Call the teacher in-process instead of through a forked timeout worker.", + ) + parser.add_argument("--start-index", type=int, default=0, help="First synthetic case index for this shard.") + parser.add_argument("--index-stride", type=int, default=1, help="Synthetic case index stride for disjoint shards.") + parser.add_argument( + "--exclusion-eval", + action="append", + type=Path, + default=None, + help="Eval JSONL to reject exact or near-neighbor generated training rows against.", + ) + parser.add_argument("--resume", action="store_true", help="Append until count is reached if output exists.") + parser.add_argument("--dry-run", action="store_true", help="Use deterministic fallback instead of teacher calls.") + parser.add_argument("--log-rejections", action="store_true", help="Print JSONL progress for rejected candidates.") + args = parser.parse_args(argv) + + if args.count <= 0: + raise SystemExit("--count must be positive") + if args.start_index < 0: + raise SystemExit("--start-index must be non-negative") + if args.index_stride <= 0: + raise SystemExit("--index-stride must be positive") + if args.teacher_error_retries < 0: + raise SystemExit("--teacher-error-retries must be non-negative") + if args.teacher_error_sleep_seconds < 0: + raise SystemExit("--teacher-error-sleep-seconds must be non-negative") + paths = dataset_paths(args.dataset_version) + args.output = args.output or paths["output"] + args.manifest = args.manifest or paths["manifest"] + args.case_specs = args.case_specs or paths["case_specs"] + + cards = load_protocol_cards() + cards_by_id = {str(card["card_id"]): card for card in cards} + missing_cards = sorted({*CLINICAL_CARD_IDS, SAFETY_CARD_ID, SBAR_CARD_ID} - set(cards_by_id)) + if missing_cards: + raise SystemExit(f"missing protocol cards: {', '.join(missing_cards)}") + exclusion_paths = _exclusion_paths_for_generation(args.dataset_version, args.exclusion_eval) + exclusion_signatures = load_exclusion_signatures(exclusion_paths) + + existing_rows = _load_existing_rows(args.output) if args.resume else [] + accepted: list[dict[str, Any]] = list(existing_rows) + accepted_ids = {row.get("case_id") for row in accepted} + manifest_events: list[dict[str, Any]] = [] + counters: Counter[str] = Counter() + candidate_totals: Counter[str] = Counter() + rejection_reasons: Counter[str] = Counter() + for row in accepted: + category = str(row.get("category") or row.get("metadata", {}).get("failure_class") or "unknown") + counters[category] += 1 + counters.update(f"tag:{tag}" for tag in row.get("tags", [])) + metadata = row.get("metadata", {}) + candidate_totals["total"] += int(metadata.get("pass_rate_total") or 0) + candidate_totals["passed"] += int(metadata.get("pass_rate_passed") or 0) + + client = _teacher_client(args.teacher_model_id, args.timeout_seconds, args.teacher_max_tokens) if not args.dry_run else None + started_at = datetime.now(UTC) + max_attempts = args.max_attempts or args.count * 4 + attempt_index = 0 + + args.output.parent.mkdir(parents=True, exist_ok=True) + args.case_specs.parent.mkdir(parents=True, exist_ok=True) + mode = "a" if args.resume and args.output.exists() else "w" + spec_mode = "a" if args.resume and args.case_specs.exists() else "w" + + with args.output.open(mode, encoding="utf-8") as output_file, args.case_specs.open(spec_mode, encoding="utf-8") as spec_file: + while len(accepted) < args.count and attempt_index < max_attempts: + case_index = case_index_for_attempt( + attempt_index, + start_index=args.start_index, + index_stride=args.index_stride, + ) + attempt_index += 1 + spec = generate_case_spec(case_index, cards_by_id, dataset_version=args.dataset_version) + if spec.case_id in accepted_ids: + continue + exclusion_match = _eval_exclusion_neighbor(spec, exclusion_signatures) + if exclusion_match: + rejection_reasons[exclusion_match["reason"]] += 1 + manifest_events.append( + { + "case_id": spec.case_id, + "failure_class": spec.failure_class, + "accepted": False, + **exclusion_match, + } + ) + if args.log_rejections: + _print_progress_event( + { + "accepted": len(accepted), + "target": args.count, + "case_id": spec.case_id, + "failure_class": spec.failure_class, + **exclusion_match, + } + ) + continue + prepared = prepare_case(spec, cards_by_id) + harness_gap = _harness_retrieval_gap(prepared) + if harness_gap: + rejection_reasons[harness_gap["reason"]] += 1 + manifest_events.append( + { + "case_id": spec.case_id, + "failure_class": spec.failure_class, + "accepted": False, + **harness_gap, + } + ) + if args.log_rejections: + _print_progress_event( + { + "accepted": len(accepted), + "target": args.count, + "case_id": spec.case_id, + "failure_class": spec.failure_class, + **harness_gap, + } + ) + continue + candidate_count = args.high_risk_candidate_count if spec.high_risk else args.candidate_count + candidate_count = max(1, min(candidate_count, 12)) + try: + raw_candidates = _raw_candidates_with_retries( + client=client, + prepared=prepared, + teacher_model_id=args.teacher_model_id, + candidate_count=candidate_count, + dry_run=args.dry_run, + use_worker=not args.no_teacher_worker, + teacher_error_retries=args.teacher_error_retries, + teacher_error_sleep_seconds=args.teacher_error_sleep_seconds, + ) + except ModelClientError as exc: + rejection_reasons["teacher_backend_error"] += 1 + safe_error = _safe_error_text(str(exc)) + manifest_events.append( + { + "case_id": spec.case_id, + "failure_class": spec.failure_class, + "accepted": False, + "reason": safe_error, + } + ) + if args.log_rejections: + _print_progress_event( + { + "accepted": len(accepted), + "target": args.count, + "case_id": spec.case_id, + "failure_class": spec.failure_class, + "reason": "teacher_backend_error", + "error": safe_error, + } + ) + continue + + candidate_results = [score_candidate(candidate, prepared) for candidate in raw_candidates] + if not candidate_results: + rejection_reasons["no_candidates"] += 1 + if args.log_rejections: + _print_progress_event( + { + "accepted": len(accepted), + "target": args.count, + "case_id": spec.case_id, + "failure_class": spec.failure_class, + "reason": "no_candidates", + } + ) + continue + best = max(candidate_results, key=lambda item: (item.passed, item.reward_score, -len(item.patched_fields))) + passed_count = sum(1 for item in candidate_results if item.passed) + candidate_totals["total"] += len(candidate_results) + candidate_totals["passed"] += passed_count + if not best.passed: + failure_key = _rejection_key(best) + policy_issues = _policy_issues_for_prepared(best.output, prepared) + rejection_reasons[failure_key] += 1 + manifest_events.append( + { + "case_id": spec.case_id, + "failure_class": spec.failure_class, + "accepted": False, + "reason": failure_key, + "validation_failures": best.validation.get("failures", []), + "expected_label_score": best.expected_label_score, + "reward_components": best.reward_components, + "policy_issues": policy_issues, + } + ) + if args.log_rejections: + _print_progress_event( + { + "accepted": len(accepted), + "target": args.count, + "case_id": spec.case_id, + "failure_class": spec.failure_class, + "reason": failure_key, + "validation_failures": best.validation.get("failures", [])[:3], + "expected_label_failed": [ + key for key, value in best.expected_label_score.items() if value is False + ][:5], + "failed_rewards": [key for key, value in best.reward_components.items() if not value], + "policy_issues": policy_issues[:8], + } + ) + continue + + row = build_sft_row( + prepared=prepared, + result=best, + teacher_model_id=args.teacher_model_id, + candidate_total=len(candidate_results), + candidate_passed=passed_count, + ) + output_file.write(json.dumps(row, sort_keys=True) + "\n") + output_file.flush() + spec_file.write(json.dumps(case_spec_record(prepared), sort_keys=True) + "\n") + spec_file.flush() + accepted.append(row) + accepted_ids.add(spec.case_id) + counters[spec.failure_class] += 1 + counters.update(f"tag:{tag}" for tag in spec.tags) + manifest_events.append( + { + "case_id": spec.case_id, + "failure_class": spec.failure_class, + "accepted": True, + "candidate_total": len(candidate_results), + "candidate_passed": passed_count, + "reward_score": best.reward_score, + "patched_fields": best.patched_fields, + } + ) + print( + json.dumps( + { + "accepted": len(accepted), + "target": args.count, + "case_id": spec.case_id, + "failure_class": spec.failure_class, + "candidate_passed": passed_count, + "candidate_total": len(candidate_results), + }, + sort_keys=True, + ), + flush=True, + ) + + manifest = build_manifest( + output_path=args.output, + case_specs_path=args.case_specs, + dataset_version=args.dataset_version, + rows=accepted, + started_at=started_at, + teacher_model_id=args.teacher_model_id, + dry_run=args.dry_run, + attempts=attempt_index, + start_index=args.start_index, + index_stride=args.index_stride, + counters=counters, + candidate_totals=candidate_totals, + rejection_reasons=rejection_reasons, + events=manifest_events, + exclusion_paths=exclusion_paths, + exclusion_signature_count=len(exclusion_signatures), + ) + args.manifest.parent.mkdir(parents=True, exist_ok=True) + args.manifest.write_text(json.dumps(manifest, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps({"manifest": str(args.manifest), "rows": len(accepted), "attempts": attempt_index}, sort_keys=True)) + return 0 if len(accepted) >= args.count else 1 + + +def _teacher_client(teacher_model_id: str, timeout_seconds: float, max_tokens: int) -> TeacherClient: + base = load_config() + openrouter = _openrouter_config_for_teacher_model(teacher_model_id) + if openrouter: + endpoint, api_key = openrouter + return TeacherClient( + endpoint=endpoint, + model_id=teacher_model_id, + auth_headers={"Authorization": f"Bearer {api_key}"}, + timeout_seconds=timeout_seconds, + max_tokens=max(64, max_tokens), + endpoint_env="OPENROUTER_BASE_URL", + api_key_env="OPENROUTER_API_KEY", + ) + + config = replace(base, model_backend="hosted_omni", nvidia_model_id=teacher_model_id).validated() + endpoint = config.omni_endpoint_url or config.hf_endpoint_url or config.nvidia_base_url + if not endpoint: + raise ModelClientError("teacher model requires NVIDIA_BASE_URL, OMNI_ENDPOINT_URL, or HF_ENDPOINT_URL") + auth_headers: dict[str, str] = {} + endpoint_env = _endpoint_env_name(teacher_model_id) + api_key_env = "" + if "integrate.api.nvidia.com" in endpoint: + if not config.nvidia_api_key: + raise ModelClientError("teacher NVIDIA endpoint requires NVIDIA_API_KEY") + auth_headers["Authorization"] = f"Bearer {config.nvidia_api_key}" + api_key_env = "NVIDIA_API_KEY" + elif config.hf_token: + auth_headers["Authorization"] = f"Bearer {config.hf_token}" + api_key_env = "HF_TOKEN" + return TeacherClient( + endpoint=endpoint, + model_id=teacher_model_id, + auth_headers=auth_headers, + timeout_seconds=timeout_seconds, + max_tokens=max(64, max_tokens), + endpoint_env=endpoint_env, + api_key_env=api_key_env, + ) + + +def _openrouter_config_for_teacher_model(teacher_model_id: str) -> tuple[str, str] | None: + configured_model = os.getenv("OPENROUTER_FREE_MODEL_ID", "").strip() + if configured_model and teacher_model_id != configured_model: + return None + if not configured_model and not teacher_model_id.endswith(":free"): + return None + endpoint = os.getenv("OPENROUTER_BASE_URL", "").strip() + api_key = os.getenv("OPENROUTER_API_KEY", "").strip() + if not endpoint and not api_key: + return None + if not endpoint: + raise ModelClientError("OpenRouter teacher model requires OPENROUTER_BASE_URL") + if not api_key: + raise ModelClientError("OpenRouter teacher model requires OPENROUTER_API_KEY") + return endpoint, api_key + + +def generate_case_spec( + index: int, + cards_by_id: dict[str, dict[str, Any]], + *, + dataset_version: str = DATASET_VERSION, +) -> SyntheticCase: + failure_class = _failure_class_for_index(index, dataset_version=dataset_version) + if uses_v13_perfect_eval_policy(dataset_version): + return _generate_v13_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + if uses_v12_perfect_eval_policy(dataset_version): + return _generate_v12_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + if uses_v10_perfect_eval_policy(dataset_version): + return _generate_v10_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + if uses_v9_perfect_eval_policy(dataset_version): + return _generate_v9_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + if uses_v8_multirule_policy(dataset_version): + return _generate_v8_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + if uses_v7_source_card_policy(dataset_version): + return _generate_v7_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + if uses_v6_observation_policy(dataset_version): + return _generate_v6_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + if uses_v5_focused_policy(dataset_version): + return _generate_v5_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + if uses_v3_field_workflow_policy(dataset_version): + return _generate_v3_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + + if failure_class == "negation_safety_boundary": + target = SAFETY_CARD_ID + intake = _negated_intake(index) + tags = ["negation", "safety_boundary"] + high_risk = True + elif failure_class == "forbidden_instruction_avoidance": + target = SAFETY_CARD_ID + intake = _forbidden_intake(index) + tags = ["forbidden_instruction", "safety_boundary"] + high_risk = True + elif failure_class == "sbar_grounding": + target = SBAR_CARD_ID + card_id = CLINICAL_CARD_IDS[index % len(CLINICAL_CARD_IDS)] + intake = _positive_intake(card_id, index, handoff=True) + tags = ["sbar", _tag_for_card(card_id)] + high_risk = True + elif failure_class == "fallback_rescue_shape": + target, intake = _fallback_rescue_intake(index) + tags = ["fallback_rescue", _tag_for_card(target)] + high_risk = True + else: + card_id = CLINICAL_CARD_IDS[index % len(CLINICAL_CARD_IDS)] + target = card_id + intake = _positive_intake(card_id, index, handoff=False) + tags = [_tag_for_card(card_id), failure_class] + high_risk = failure_class == "source_card_candidate_pathway" + + return SyntheticCase( + case_id=f"{dataset_version}-{index:06d}", + dataset_version=dataset_version, + failure_class=failure_class, + target_protocol_card_id=target, + structured_intake=intake, + tags=tags, + high_risk=high_risk, + ) + + +def _generate_v8_case_spec( + index: int, + cards_by_id: dict[str, dict[str, Any]], + *, + dataset_version: str, + failure_class: str, +) -> SyntheticCase: + target = "FEVER-RED-FLAGS-v1" + source_index = index + 2400 + intake = _multi_rule_observation_ownership_intake(source_index, failure_class=failure_class) + intake = _apply_v3_workflow_context( + intake, + index=index, + category=failure_class, + target_card_id=target, + dataset_version=dataset_version, + ) + intake["multi_rule_observation_focus"] = ( + "Gold output must cite FEVER-RED-FLAGS-v1 and every fired pregnancy/postpartum rule card, " + "select all required-observation target ids for those clinical source cards, and make each selected " + "observation visible before deterministic scaffolding would fill it." + ) + if failure_class == "multi_rule_candidate_focus": + intake["candidate_pathway_focus"] = ( + "Keep candidate_protocol_pathways focused on the primary FEVER target while keeping the fired " + "PREG source card and its required observations visible in source_cards and observation fields." + ) + + if target not in cards_by_id: + raise KeyError(f"missing target card for v8 spec: {target}") + + return SyntheticCase( + case_id=f"{dataset_version}-{index:06d}", + dataset_version=dataset_version, + failure_class=failure_class, + target_protocol_card_id=target, + structured_intake=intake, + tags=_dedupe( + [ + "field_workflow", + "v8", + "multi_rule_observation_ownership", + "fever_red_flags", + "preg_danger_signs", + _field_tag_for_category(failure_class), + ] + ), + high_risk=True, + ) + + +def _generate_v10_case_spec( + index: int, + cards_by_id: dict[str, dict[str, Any]], + *, + dataset_version: str, + failure_class: str, +) -> SyntheticCase: + target = "FEVER-RED-FLAGS-v1" + if uses_v14_perfect_eval_policy(dataset_version): + source_index = index + 13200 + elif uses_v13_perfect_eval_policy(dataset_version): + source_index = index + 11200 + elif uses_v12_perfect_eval_policy(dataset_version): + source_index = index + 9200 + elif uses_v11_perfect_eval_policy(dataset_version): + source_index = index + 7200 + else: + source_index = index + 5200 + workflow_category = _v10_postpartum_workflow_category(index, failure_class) + intake = _postpartum_fever_required_obs_intake(source_index, failure_class=failure_class) + if uses_v13_perfect_eval_policy(dataset_version): + symptoms = str(intake.get("symptoms") or "") + for phrase in ( + ", no chest pain reported", + "; chest pain denied", + "; no chest pressure reported", + ): + symptoms = symptoms.replace(phrase, "") + intake["symptoms"] = symptoms + intake = _apply_v3_workflow_context( + intake, + index=index, + category=workflow_category, + target_card_id=target, + dataset_version=dataset_version, + ) + intake["v10_training_focus"] = ( + "Prior local v9 outputs cited FEVER-RED-FLAGS-v1 and PREG-DANGER-SIGNS-v1 but selected only " + "FEVER required-observation ids, so deterministic scaffolding filled the pregnancy danger-sign " + "observations. Gold output must select every non-exempt FEVER and PREG required-observation id, " + "and visible observation text for both cards must already appear in missing_info_to_collect and " + "next_observations_to_collect before deterministic scaffolding." + ) + intake["cross_card_observation_closure_focus"] = ( + "When a secondary fired clinical card is in source_cards or candidate_protocol_pathways, close its " + "required observations too. Do not stop observation planning at the target FEVER card." + ) + if uses_v11_perfect_eval_policy(dataset_version): + intake["v11_training_focus"] = ( + "Prior local v10 outputs selected every FEVER and PREG required-observation id but only wrote the " + "FEVER-side cues plus pregnancy status into visible observation fields. Gold output must front-load " + "PREG-DANGER-SIGNS-v1 visible cues in both missing_info_to_collect and next_observations_to_collect: " + "pregnancy or postpartum status, bleeding report, abdominal pain report, headache or vision symptoms, " + "seizure or fainting report, and fever report. Do not rely on selected_required_observation_ids alone." + ) + if uses_v12_perfect_eval_policy(dataset_version): + intake["v12_training_focus"] = ( + "V12 resumes from the v10 adapter, not v11. Preserve v10 source-card, schema, urgency, red-flag, " + "and handoff behavior while fixing the remaining postpartum FEVER plus PREG visible observation gap. " + "Gold output must select every FEVER and PREG required-observation id and make each cue visible in " + "both missing_info_to_collect and next_observations_to_collect without deterministic scaffold fill." + ) + if uses_v13_perfect_eval_policy(dataset_version): + intake["v13_training_focus"] = ( + "V12 still produced a few FEVER/PREG holdout rows where source_cards and candidate_protocol_pathways " + "included PREG-DANGER-SIGNS-v1, but visible observation fields only contained FEVER-side cues until " + "deterministic repair. Gold output must put the PREG danger-sign cues directly into both " + "missing_info_to_collect and next_observations_to_collect whenever PREG-DANGER-SIGNS-v1 appears in " + "source_cards or candidate_protocol_pathways: pregnancy or postpartum status, bleeding report, " + "abdominal pain report, headache or vision symptoms, seizure or fainting report, and fever report. " + "Selected_required_observation_ids are necessary but not sufficient." + ) + intake["v13_visible_observation_contract"] = { + "failure_to_avoid": "FEVER-only missing_info_to_collect or next_observations_to_collect is incorrect when PREG is cited.", + "preg_cues_required_in_missing_info_to_collect": [ + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + ], + "preg_cues_required_in_next_observations_to_collect": [ + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + ], + } + if uses_v14_perfect_eval_policy(dataset_version): + intake["v14_training_focus"] = ( + "V13 only trained on a partial delta and still required deterministic patches on FEVER plus PREG " + "observation fields. Preserve v12/v10 source-card and schema behavior while fully covering the " + "visible PREG danger-sign cues in both missing_info_to_collect and next_observations_to_collect." + ) + if failure_class == "postpartum_fever_required_obs_candidate_focus": + intake["candidate_pathway_focus"] = ( + "Keep candidate_protocol_pathways to FEVER-RED-FLAGS-v1 and the fired PREG-DANGER-SIGNS-v1 card; " + "avoid unrelated retrieved distractor cards." + ) + if failure_class == "postpartum_fever_required_obs_candidate_and_source_closure": + intake["candidate_pathway_focus"] = ( + "Keep candidate_protocol_pathways to FEVER-RED-FLAGS-v1 and the fired PREG-DANGER-SIGNS-v1 card, " + "and keep source_cards closed over FEVER, PREG, SAFETY, and REFERRAL support cards." + ) + if failure_class == "postpartum_fever_required_obs_visible_preg_candidate_pathway_closure": + intake["candidate_pathway_focus"] = ( + "Candidate pathways must include FEVER-RED-FLAGS-v1 and PREG-DANGER-SIGNS-v1, and the visible " + "observation fields must include the PREG danger-sign cues even though FEVER remains the target." + ) + if failure_class == "postpartum_fever_required_obs_selected_id_compressed_field_repair": + intake["selected_id_visible_text_repair_focus"] = ( + "Do not compress the answer into selected_required_observation_ids only. The responder-facing " + "missing and next-observation lists must spell out the PREG danger-sign observations before scaffold fill." + ) + + if target not in cards_by_id: + raise KeyError(f"missing target card for v10 spec: {target}") + + return SyntheticCase( + case_id=f"{dataset_version}-{index:06d}", + dataset_version=dataset_version, + failure_class=failure_class, + target_protocol_card_id=target, + structured_intake=intake, + tags=_dedupe( + [ + "field_workflow", + ( + "v14" + if uses_v14_perfect_eval_policy(dataset_version) + else "v13" + if uses_v13_perfect_eval_policy(dataset_version) + else "v12" + if uses_v12_perfect_eval_policy(dataset_version) + else "v11" + if uses_v11_perfect_eval_policy(dataset_version) + else "v10" + ), + "postpartum_fever_required_obs", + "multi_rule_observation_ownership", + "required_observation_ownership", + "dual_field_observation_closure", + *( + ["visible_observation_text_closure", "preg_danger_signs_front_loaded"] + if ( + uses_v11_perfect_eval_policy(dataset_version) + or uses_v12_perfect_eval_policy(dataset_version) + or uses_v13_perfect_eval_policy(dataset_version) + ) + else [] + ), + "fever_red_flags", + "preg_danger_signs", + _field_tag_for_category(workflow_category), + failure_class, + ] + ), + high_risk=True, + ) + + +def _generate_v13_case_spec( + index: int, + cards_by_id: dict[str, dict[str, Any]], + *, + dataset_version: str, + failure_class: str, +) -> SyntheticCase: + postpartum_classes = { + "postpartum_fever_required_obs_visible_preg_source_card_cue_closure", + "postpartum_fever_required_obs_visible_preg_candidate_pathway_closure", + "postpartum_fever_required_obs_selected_id_compressed_field_repair", + } + if failure_class in postpartum_classes: + return _generate_v10_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + if failure_class == "wound_source_card_schema_replay": + return _generate_v12_wound_replay_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + if failure_class == "referral_candidate_pathway_replay": + return _generate_v12_referral_replay_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + raise ValueError(f"unsupported v13 failure class: {failure_class}") + + +def _generate_v12_case_spec( + index: int, + cards_by_id: dict[str, dict[str, Any]], + *, + dataset_version: str, + failure_class: str, +) -> SyntheticCase: + postpartum_classes = { + "postpartum_fever_required_obs_dual_card_selected_ids_visible_fields", + "postpartum_fever_required_obs_candidate_and_source_closure", + } + if failure_class in postpartum_classes: + return _generate_v10_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + if failure_class == "wound_source_card_schema_replay": + return _generate_v12_wound_replay_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + if failure_class == "referral_candidate_pathway_replay": + return _generate_v12_referral_replay_case_spec( + index, + cards_by_id, + dataset_version=dataset_version, + failure_class=failure_class, + ) + raise ValueError(f"unsupported v12 failure class: {failure_class}") + + +def _generate_v12_wound_replay_case_spec( + index: int, + cards_by_id: dict[str, dict[str, Any]], + *, + dataset_version: str, + failure_class: str, +) -> SyntheticCase: + target = "WOUND-INFECTION-ESCALATION-v1" + if uses_v14_perfect_eval_policy(dataset_version): + version_label = "v14" + source_index = index + 13400 + elif uses_v13_perfect_eval_policy(dataset_version): + version_label = "v13" + source_index = index + 11400 + else: + version_label = "v12" + source_index = index + 9400 + intake = _positive_intake(target, source_index, handoff=True) + intake = _apply_v3_workflow_context( + intake, + index=index, + category="source_card_closure", + target_card_id=target, + dataset_version=dataset_version, + ) + intake[f"{version_label}_training_focus"] = ( + f"Replay v10-passing wound behavior while training {version_label}. Gold output must keep the complete " + "navigator schema, cite WOUND-INFECTION-ESCALATION-v1, SAFETY-BOUNDARIES-v1, and REFERRAL-SBAR-v1 in " + "source_cards, select wound required-observation ids, and keep the SBAR grounded in wound facts without " + "hallucinated pregnancy." + ) + intake["source_card_closure_focus"] = ( + "Wound rows protect source-card closure and schema completion while preserving a clinical candidate pathway." + ) + if target not in cards_by_id: + raise KeyError(f"missing target card for {version_label} wound spec: {target}") + return SyntheticCase( + case_id=f"{dataset_version}-{index:06d}", + dataset_version=dataset_version, + failure_class=failure_class, + target_protocol_card_id=target, + structured_intake=intake, + tags=_dedupe( + [ + "field_workflow", + version_label, + "wound_replay", + "source_card_closure", + "schema_completion", + "handoff_grounding", + "wound_infection", + ] + ), + high_risk=True, + ) + + +def _generate_v12_referral_replay_case_spec( + index: int, + cards_by_id: dict[str, dict[str, Any]], + *, + dataset_version: str, + failure_class: str, +) -> SyntheticCase: + target = SBAR_CARD_ID + if uses_v14_perfect_eval_policy(dataset_version): + version_label = "v14" + source_index = index + 13600 + elif uses_v13_perfect_eval_policy(dataset_version): + version_label = "v13" + source_index = index + 11600 + else: + version_label = "v12" + source_index = index + 9600 + intake = _postpartum_fever_required_obs_intake(source_index, failure_class=failure_class) + intake = _apply_v3_workflow_context( + intake, + index=index, + category="sbar_source_coupling", + target_card_id=target, + dataset_version=dataset_version, + ) + intake[f"{version_label}_training_focus"] = ( + f"Replay the v10-passing referral/SBAR pathway shape while training {version_label}. Gold output must keep " + "REFERRAL-SBAR-v1 as the target candidate pathway while also retaining fired FEVER and PREG clinical pathways " + "before deterministic candidate scaffolding. Source cards must stay closed over REFERRAL, SAFETY, FEVER, and " + "PREG support." + ) + intake["candidate_pathway_focus"] = ( + "Candidate pathways should include REFERRAL-SBAR-v1 plus fired FEVER and PREG clinical cards; avoid unrelated " + "distractor cards." + ) + if target not in cards_by_id: + raise KeyError(f"missing target card for {version_label} referral spec: {target}") + return SyntheticCase( + case_id=f"{dataset_version}-{index:06d}", + dataset_version=dataset_version, + failure_class=failure_class, + target_protocol_card_id=target, + structured_intake=intake, + tags=_dedupe( + [ + "field_workflow", + version_label, + "referral_candidate_replay", + "sbar_source_coupling", + "candidate_pathway_replay", + "fever_red_flags", + "preg_danger_signs", + ] + ), + high_risk=True, + ) + + +def _generate_v9_case_spec( + index: int, + cards_by_id: dict[str, dict[str, Any]], + *, + dataset_version: str, + failure_class: str, +) -> SyntheticCase: + target = "FEVER-RED-FLAGS-v1" + source_index = index + 3200 + workflow_category = _v9_postpartum_workflow_category(index, failure_class) + intake = _postpartum_fever_required_obs_intake(source_index, failure_class=failure_class) + intake = _apply_v3_workflow_context( + intake, + index=index, + category=workflow_category, + target_card_id=target, + dataset_version=dataset_version, + ) + intake["v9_training_focus"] = ( + "Gold output must treat FEVER-RED-FLAGS-v1 and PREG-DANGER-SIGNS-v1 as jointly fired clinical " + "source cards. It must select every mandatory required-observation target id for both cards and copy " + "each mandatory_required_observation_targets display_text into missing_info_to_collect before any " + "deterministic scaffold could fill the field." + ) + if failure_class == "postpartum_fever_required_obs_candidate_focus": + intake["candidate_pathway_focus"] = ( + "Keep candidate_protocol_pathways focused on FEVER-RED-FLAGS-v1 plus the fired PREG-DANGER-SIGNS-v1 " + "card; do not add unrelated distractors." + ) + + if target not in cards_by_id: + raise KeyError(f"missing target card for v9 spec: {target}") + + return SyntheticCase( + case_id=f"{dataset_version}-{index:06d}", + dataset_version=dataset_version, + failure_class=failure_class, + target_protocol_card_id=target, + structured_intake=intake, + tags=_dedupe( + [ + "field_workflow", + "v9", + "postpartum_fever_required_obs", + "multi_rule_observation_ownership", + "required_observation_ownership", + "fever_red_flags", + "preg_danger_signs", + _field_tag_for_category(workflow_category), + failure_class, + ] + ), + high_risk=True, + ) + + +def _generate_v7_case_spec( + index: int, + cards_by_id: dict[str, dict[str, Any]], + *, + dataset_version: str, + failure_class: str, +) -> SyntheticCase: + card_id = CLINICAL_CARD_IDS[index % len(CLINICAL_CARD_IDS)] + target = card_id + source_index = index + 1600 + handoff = True + + if failure_class == "source_card_closure" and index % 4 == 0: + triad = ("PREG-DANGER-SIGNS-v1", "CHEST-PAIN-ESCALATION-v1", "FEVER-RED-FLAGS-v1") + target = triad[(index // 4) % len(triad)] + card_id = target + intake = _multi_rule_source_closure_intake(source_index) + else: + if failure_class == "sbar_source_coupling": + target = SBAR_CARD_ID + card_id = _pick( + ( + "CHEST-PAIN-ESCALATION-v1", + "PREG-DANGER-SIGNS-v1", + "RESP-DISTRESS-RED-FLAGS-v1", + "STROKE-SIGNS-v1", + ), + index, + ) + elif failure_class == "distractor_card_resistance": + target = _pick( + ( + "CHEST-PAIN-ESCALATION-v1", + "FEVER-RED-FLAGS-v1", + "PREG-DANGER-SIGNS-v1", + "STROKE-SIGNS-v1", + ), + index, + ) + card_id = target + elif failure_class == "observation_source_joint": + target = _pick(CLINICAL_CARD_IDS, index + 3) + card_id = target + intake = _positive_intake(card_id, source_index, handoff=handoff) + + intake = _apply_v3_workflow_context( + intake, + index=index, + category=failure_class, + target_card_id=target, + dataset_version=dataset_version, + ) + if failure_class == "source_card_closure": + intake["source_card_closure_focus"] = ( + "Gold output must cite every clinical target it relies on plus SAFETY-BOUNDARIES-v1 for protocol-only " + "safety text and REFERRAL-SBAR-v1 for the SBAR handoff." + ) + elif failure_class == "observation_source_joint": + intake["observation_source_joint_focus"] = ( + "Gold output must keep selected required-observation ids visible in observation text while also closing " + "clinical, safety, and SBAR source-card citations." + ) + elif failure_class == "distractor_card_resistance": + intake["distractor_card_focus"] = ( + "Retrieved context may include distractor protocol cards. Cite the target, safety, and SBAR support cards " + "without adding irrelevant clinical source cards." + ) + elif failure_class == "sbar_source_coupling": + intake["sbar_source_focus"] = ( + "Gold output must make the SBAR handoff concise and cite REFERRAL-SBAR-v1 alongside the clinical and " + "safety cards that support the handoff." + ) + + tag = _tag_for_card(card_id if target in {SAFETY_CARD_ID, SBAR_CARD_ID} else target) + tags = ["field_workflow", "v7", _field_tag_for_category(failure_class), tag, "source_card_closure"] + if target == SBAR_CARD_ID: + tags.append("sbar") + if target == SAFETY_CARD_ID: + tags.append("safety_boundary") + if failure_class == "distractor_card_resistance": + tags.append("distractor_resistance") + if failure_class == "observation_source_joint": + tags.append("required_observation_ownership") + + if target not in cards_by_id and target not in {SAFETY_CARD_ID, SBAR_CARD_ID}: + raise KeyError(f"missing target card for v7 spec: {target}") + + return SyntheticCase( + case_id=f"{dataset_version}-{index:06d}", + dataset_version=dataset_version, + failure_class=failure_class, + target_protocol_card_id=target, + structured_intake=intake, + tags=_dedupe(tags), + high_risk=True, + ) + + +def _generate_v6_case_spec( + index: int, + cards_by_id: dict[str, dict[str, Any]], + *, + dataset_version: str, + failure_class: str, +) -> SyntheticCase: + card_id = CLINICAL_CARD_IDS[index % len(CLINICAL_CARD_IDS)] + target = card_id + handoff = index % 4 == 0 + source_index = index + 1200 + + if failure_class == "observation_correction": + source_index = index + 1300 + handoff = index % 3 == 0 + elif failure_class == "v6_preservation": + target = _pick([card_id, SBAR_CARD_ID, SAFETY_CARD_ID], index) + handoff = target == SBAR_CARD_ID or index % 3 == 0 + source_index = index + 1400 + + if target == SAFETY_CARD_ID: + intake = _negated_intake(source_index) + else: + intake = _positive_intake(card_id, source_index, handoff=handoff) + + intake = _apply_v3_workflow_context( + intake, + index=index, + category=failure_class, + target_card_id=target, + dataset_version=dataset_version, + ) + if failure_class == "observation_correction": + intake["previous_model_failure_note"] = ( + "Prior local output duplicated missing and next observation lists or treated harness metadata as " + "medic observations. Gold output must rewrite those fields as clinical observation work only." + ) + elif failure_class == "required_observation_ownership": + intake["required_observation_focus"] = ( + "Gold output must select required_observation_targets and express them as concrete responder-facing " + "missing and next observations before deterministic scaffolding would fill them." + ) + elif failure_class == "v6_preservation": + intake["preservation_focus"] = ( + "Preserve v5 source-card, SBAR, urgency, red-flag, low-resource, and safety behavior while keeping " + "observation fields free of harness metadata." + ) + + tag = _tag_for_card(card_id if target in {SAFETY_CARD_ID, SBAR_CARD_ID} else target) + tags = ["field_workflow", "v6", _field_tag_for_category(failure_class), tag] + if target == SAFETY_CARD_ID: + tags.append("safety_boundary") + if target == SBAR_CARD_ID: + tags.append("sbar") + if failure_class == "observation_correction": + tags.append("teacher_rewrite_correction") + + if target not in cards_by_id and target not in {SAFETY_CARD_ID, SBAR_CARD_ID}: + raise KeyError(f"missing target card for v6 spec: {target}") + + return SyntheticCase( + case_id=f"{dataset_version}-{index:06d}", + dataset_version=dataset_version, + failure_class=failure_class, + target_protocol_card_id=target, + structured_intake=intake, + tags=_dedupe(tags), + high_risk=True, + ) + + +def _generate_v5_case_spec( + index: int, + cards_by_id: dict[str, dict[str, Any]], + *, + dataset_version: str, + failure_class: str, +) -> SyntheticCase: + card_id = CLINICAL_CARD_IDS[index % len(CLINICAL_CARD_IDS)] + target = card_id + handoff = index % 3 == 0 + source_index = index + 700 + + if failure_class == "sbar_observation_ownership": + target = SBAR_CARD_ID + handoff = True + source_index = index + 800 + elif failure_class == "source_card_invariant": + target = ("STROKE-SIGNS-v1", "PREG-DANGER-SIGNS-v1")[index % 2] + card_id = target + handoff = index % 4 == 0 + source_index = index + 900 + elif failure_class == "noisy_field_audio_style": + handoff = index % 2 == 0 + source_index = index + 1000 + elif failure_class == "general_regression": + target = _pick([card_id, SBAR_CARD_ID, SAFETY_CARD_ID], index) + handoff = target == SBAR_CARD_ID or index % 4 == 0 + source_index = index + 1100 + + if target == SAFETY_CARD_ID: + intake = _negated_intake(source_index) + else: + intake = _positive_intake(card_id, source_index, handoff=handoff) + + if failure_class == "noisy_field_audio_style": + intake["responder_note"] = ( + str(intake.get("responder_note") or "").strip() + + " Confirmed ASR-like field note: punctuation was sparse, repeated words were removed, " + "and the responder accepted these fields before navigation." + ).strip() + intake["transcript_quality"] = "confirmed_noisy_field_audio" + + intake = _apply_v3_workflow_context( + intake, + index=index, + category=failure_class, + target_card_id=target, + dataset_version=dataset_version, + ) + tag = _tag_for_card(card_id if target in {SAFETY_CARD_ID, SBAR_CARD_ID} else target) + tags = ["field_workflow", "v5", _field_tag_for_category(failure_class), tag] + if target == SAFETY_CARD_ID: + tags.append("safety_boundary") + if target == SBAR_CARD_ID: + tags.append("sbar") + if failure_class == "source_card_invariant": + tags.append("fired_rule_source_card") + + if target not in cards_by_id and target not in {SAFETY_CARD_ID, SBAR_CARD_ID}: + raise KeyError(f"missing target card for v5 spec: {target}") + + return SyntheticCase( + case_id=f"{dataset_version}-{index:06d}", + dataset_version=dataset_version, + failure_class=failure_class, + target_protocol_card_id=target, + structured_intake=intake, + tags=_dedupe(tags), + high_risk=True, + ) + + +def _generate_v3_case_spec( + index: int, + cards_by_id: dict[str, dict[str, Any]], + *, + dataset_version: str, + failure_class: str, +) -> SyntheticCase: + card_id = CLINICAL_CARD_IDS[index % len(CLINICAL_CARD_IDS)] + high_risk = failure_class in { + "radio_handoff", + "escalation_precision", + "sbar_handoff_usefulness", + "source_card_discipline", + "low_resource_constraints", + "workflow_repair_seed", + } + + if failure_class in {"radio_handoff", "sbar_handoff_usefulness"}: + target = SBAR_CARD_ID + intake = _positive_intake(card_id, index + 200, handoff=True) + elif failure_class == "asr_confirmed_text": + target = card_id + intake = _positive_intake(card_id, index + 300, handoff=index % 2 == 0) + elif failure_class == "escalation_precision" and (dataset_version.startswith("figment_sft_v4") or index % 5 == 0): + target = SAFETY_CARD_ID + intake = _negated_intake(index + 400) + elif failure_class == "workflow_repair_seed": + target = SBAR_CARD_ID if index % 2 else card_id + intake = _positive_intake(card_id, index + 500, handoff=True) + else: + target = card_id + intake = _positive_intake(card_id, index + 100, handoff=False) + + intake = _apply_v3_workflow_context( + intake, + index=index, + category=failure_class, + target_card_id=target, + dataset_version=dataset_version, + ) + tag = _tag_for_card(card_id if target in {SAFETY_CARD_ID, SBAR_CARD_ID} else target) + tags = ["field_workflow", _field_tag_for_category(failure_class), tag] + if target == SAFETY_CARD_ID: + tags.append("safety_boundary") + if target == SBAR_CARD_ID: + tags.append("sbar") + + # Touch cards_by_id in this path so missing fixture cards fail near generation. + if target not in cards_by_id and target not in {SAFETY_CARD_ID, SBAR_CARD_ID}: + raise KeyError(f"missing target card for v3 spec: {target}") + + return SyntheticCase( + case_id=f"{dataset_version}-{index:06d}", + dataset_version=dataset_version, + failure_class=failure_class, + target_protocol_card_id=target, + structured_intake=intake, + tags=_dedupe(tags), + high_risk=high_risk, + ) + + +def _apply_v3_workflow_context( + intake: dict[str, Any], + *, + index: int, + category: str, + target_card_id: str, + dataset_version: str, +) -> dict[str, Any]: + updated = dict(intake) + settings = { + "rural_clinic_intake": "rural clinic intake desk with one medic", + "disaster_triage": "flood shelter disaster triage table", + "radio_handoff": "radio and runner handoff station", + "asr_confirmed_text": "mobile clinic confirmed transcript desk", + "escalation_precision": "field escalation review point", + "missing_observation_prioritization": "crowded intake line with incomplete vitals", + "sbar_handoff_usefulness": "transport coordinator radio handoff", + "source_card_discipline": "paper protocol binder review desk", + "low_resource_constraints": "remote aid post with limited equipment", + "workflow_repair_seed": "handoff repair desk after weak navigator output", + "sbar_observation_ownership": "transport coordinator SBAR handoff desk", + "required_observation_id_selection": "rural intake line with sparse observations", + "source_card_invariant": "red-flag rule audit station", + "noisy_field_audio_style": "mobile clinic confirmed audio transcript desk", + "general_regression": "mixed field workflow review station", + "required_observation_ownership": "rural intake observation-planning desk", + "observation_correction": "navigator output correction desk", + "v6_preservation": "mixed field workflow preservation review station", + "source_card_closure": "source-card closure review desk", + "observation_source_joint": "source-card and observation ownership desk", + "distractor_card_resistance": "protocol binder review desk with distractor cards", + "sbar_source_coupling": "SBAR source-card coupling handoff desk", + "multi_rule_observation_ownership": "multi-rule maternal fever observation desk", + "multi_rule_candidate_focus": "primary-pathway multi-rule review desk", + } + supplies = { + "rural_clinic_intake": "paper protocol binder, radio, shared BP cuff, no pulse oximeter", + "disaster_triage": "gloves, cot tags, paper forms, intermittent radio, no transport yet", + "radio_handoff": "runner note, radio, paper SBAR slip, no full chart", + "asr_confirmed_text": "responder-confirmed transcript, radio, paper form, no raw audio retained", + "escalation_precision": "radio, protocol binder, transport callback list, vitals partly pending", + "missing_observation_prioritization": "paper form, radio, basic vitals kit, only a few minutes per patient", + "sbar_handoff_usefulness": "radio, SBAR form, transport list, receiving clinician callback pending", + "source_card_discipline": "protocol binder with relevant and distractor cards, radio", + "low_resource_constraints": "no pulse oximeter, no BP cuff, intermittent radio only", + "workflow_repair_seed": "previous navigator output, protocol binder, radio, paper handoff form", + "sbar_observation_ownership": "SBAR form, radio, paper protocol cards, receiving callback pending", + "required_observation_id_selection": "paper intake form, radio, basic vitals kit, two-minute queue pressure", + "source_card_invariant": "deterministic red-flag sheet, protocol binder, retrieval printout", + "noisy_field_audio_style": "accepted ASR transcript, radio, paper form, no raw audio retained", + "general_regression": "protocol binder, radio, sparse vitals kit, transport callback list", + "required_observation_ownership": "required-observation target card, paper form, radio, sparse vitals kit", + "observation_correction": "previous weak navigator output, required-observation target card, radio", + "v6_preservation": "protocol binder, radio, SBAR form, sparse vitals kit, transport callback list", + "source_card_closure": "protocol binder, safety boundary card, SBAR form, radio", + "observation_source_joint": "required-observation target card, protocol binder, SBAR form, radio", + "distractor_card_resistance": "protocol binder with relevant and distractor cards, radio, SBAR slip", + "sbar_source_coupling": "SBAR form, radio, target clinical card, safety boundary card", + "multi_rule_observation_ownership": "fever card, pregnancy danger-sign card, SBAR form, radio", + "multi_rule_candidate_focus": "protocol binder with fever primary card, pregnancy source card, and distractors", + } + goals = { + "rural_clinic_intake": "speed intake and surface the next useful missing observations.", + "disaster_triage": "keep escalation and handoff useful despite noisy sparse notes.", + "radio_handoff": "turn fragmented confirmed notes into compact grounded SBAR.", + "asr_confirmed_text": "handle corrected ASR-like confirmed text without hallucinating.", + "escalation_precision": "preserve true red flags and avoid escalating denied danger words.", + "missing_observation_prioritization": "put the highest-value observations first.", + "sbar_handoff_usefulness": "make the handoff concise, grounded, and actionable.", + "source_card_discipline": "cite only relevant retrieved cards and avoid distractor leakage.", + "low_resource_constraints": "ask for alternatives when equipment is unavailable.", + "workflow_repair_seed": "repair only weak fields while preserving validated facts.", + "sbar_observation_ownership": "make SBAR depend on model-owned observation fields, not deterministic fill.", + "required_observation_id_selection": "select required observation ids and render responder-facing text.", + "source_card_invariant": "cite every deterministic fired-rule card even when retrieval is imperfect.", + "noisy_field_audio_style": "handle confirmed noisy field transcript text without hallucinating facts.", + "general_regression": "preserve v4 strengths while avoiding locked-eval overfit.", + "required_observation_ownership": "make selected required observations explicit without scaffold fill.", + "observation_correction": "rewrite weak observation fields into clinical, responder-owned observations.", + "v6_preservation": "preserve v5 strengths while correcting observation ownership.", + "source_card_closure": "close source-card citations for clinical, safety, and SBAR content.", + "observation_source_joint": "keep observation ownership while closing source-card citations.", + "distractor_card_resistance": "exclude distractor cards while citing mandatory support cards.", + "sbar_source_coupling": "make SBAR handoff depend on the SBAR source card and cited clinical facts.", + "multi_rule_observation_ownership": "own required observations for every fired clinical card.", + "multi_rule_candidate_focus": "keep primary pathway focused while owning all fired-card observations.", + } + constraints = [ + "clinician callback delayed about 20 minutes", + "radio window opens every 10 minutes", + "only one cot free and the intake line is moving", + "transport coordinator needs a one-minute handoff", + "paper form has room for only the highest-value observations", + "battery is low, so the responder needs a compact checklist", + "runner can carry only a short SBAR note", + "nearby noise makes repeated clarification likely", + ] + updated["setting"] = settings.get(category, updated.get("setting", "field workflow station")) + updated["available_supplies"] = supplies.get(category, str(updated.get("available_supplies") or "protocol binder and radio")) + updated["workflow_category"] = category + updated["field_workflow_goal"] = goals.get(category, "make field intake and handoff easier.") + updated["workflow_constraint"] = constraints[index % len(constraints)] + updated["target_protocol_card_hint"] = target_card_id + existing_note = str(updated.get("responder_note") or "").strip() + if uses_v13_perfect_eval_policy(dataset_version): + workflow_version_label = "V13" + elif uses_v12_perfect_eval_policy(dataset_version): + workflow_version_label = "V12" + elif uses_v11_perfect_eval_policy(dataset_version): + workflow_version_label = "V11" + elif uses_v10_perfect_eval_policy(dataset_version): + workflow_version_label = "V10" + elif uses_v9_perfect_eval_policy(dataset_version): + workflow_version_label = "V9" + elif uses_v8_multirule_policy(dataset_version): + workflow_version_label = "V8" + elif uses_v7_source_card_policy(dataset_version): + workflow_version_label = "V7" + elif uses_v6_observation_policy(dataset_version): + workflow_version_label = "V6" + elif uses_v5_focused_policy(dataset_version): + workflow_version_label = "V5" + else: + workflow_version_label = "V4" if dataset_version.startswith("figment_sft_v4") else "V3" + workflow_note = ( + f" {workflow_version_label} field-workflow category: {category}. " + f"Goal: {updated['field_workflow_goal']} Constraint: {updated['workflow_constraint']}. " + f"Variant {index}; synthetic and de-identified." + ) + if category == "asr_confirmed_text": + workflow_note += " Confirmed ASR-like text may have dropped punctuation, but responder confirmed the fields before navigation." + updated["transcript_quality"] = "asr_like_confirmed_text" + if category == "noisy_field_audio_style": + workflow_note += " Confirmed audio-like text may be terse or repetitive, but responder accepted it before navigation." + updated["transcript_quality"] = "confirmed_noisy_field_audio" + if category == "radio_handoff": + workflow_note += " Radio message is fragmented but confirmed by the responder." + updated["communication_channel"] = "radio_or_runner_handoff" + if category == "sbar_observation_ownership": + workflow_note += " SBAR should reuse selected observations rather than inventing assessment facts." + updated["communication_channel"] = "radio_or_runner_handoff" + if category == "source_card_invariant": + workflow_note += " Deterministic fired-rule card IDs are mandatory source cards even if retrieval ordering is weak." + if category == "required_observation_ownership": + workflow_note += " Required observation IDs and their display text must be model-owned, not scaffold-filled." + if category == "observation_correction": + workflow_note += " Correct duplicated missing/next lists and remove harness metadata from observation fields." + if category == "v6_preservation": + workflow_note += " Preserve source-card, urgency, red-flag, and SBAR behavior while keeping observations clinical." + if category == "source_card_closure": + workflow_note += " Cite clinical target, safety boundary, and SBAR cards whenever their content appears in the answer." + if category == "observation_source_joint": + workflow_note += " Required observations and source-card closure must both be model-owned." + if category == "distractor_card_resistance": + workflow_note += " Retrieved distractors are present; do not cite irrelevant clinical cards." + if category == "sbar_source_coupling": + workflow_note += " SBAR content must stay grounded in confirmed facts and REFERRAL-SBAR-v1." + if category == "multi_rule_observation_ownership": + workflow_note += " All fired clinical cards must have selected required observations visible before scaffold fill." + if category == "multi_rule_candidate_focus": + workflow_note += " Candidate pathways should include the target and fired clinical cards while avoiding unrelated distractors." + if category == "low_resource_constraints": + workflow_note += " Equipment limits must be treated as current workflow constraints, not ignored." + updated["responder_note"] = (existing_note + workflow_note).strip() + return updated + + +def _field_tag_for_category(category: str) -> str: + if category.startswith("rural_clinic"): + return "rural_clinic" + if category.startswith("disaster"): + return "disaster_response" + if category.startswith("asr"): + return "asr_like_confirmed_text" + return category + + +def _failure_distribution_for_version(dataset_version: str) -> tuple[tuple[str, int], ...]: + if uses_v14_perfect_eval_policy(dataset_version): + return V14_FAILURE_DISTRIBUTION + if uses_v13_perfect_eval_policy(dataset_version): + return V13_FAILURE_DISTRIBUTION + if uses_v12_perfect_eval_policy(dataset_version): + return V12_FAILURE_DISTRIBUTION + if uses_v11_perfect_eval_policy(dataset_version): + return V11_FAILURE_DISTRIBUTION + if uses_v10_perfect_eval_policy(dataset_version): + return V10_FAILURE_DISTRIBUTION + if uses_v9_perfect_eval_policy(dataset_version): + return V9_FAILURE_DISTRIBUTION + if uses_v8_multirule_policy(dataset_version): + return V8_FAILURE_DISTRIBUTION + if uses_v7_source_card_policy(dataset_version): + return V7_FAILURE_DISTRIBUTION + if uses_v6_observation_policy(dataset_version): + return V6_FAILURE_DISTRIBUTION + if uses_v5_focused_policy(dataset_version): + return V5_FAILURE_DISTRIBUTION + if dataset_version.startswith("figment_sft_v4"): + return V4_FAILURE_DISTRIBUTION + if uses_v3_field_workflow_policy(dataset_version): + return V3_FAILURE_DISTRIBUTION + if dataset_version == "figment_sft_v2": + return V2_FAILURE_DISTRIBUTION + return FAILURE_DISTRIBUTION + + +def _failure_class_for_index(index: int, *, dataset_version: str = DATASET_VERSION) -> str: + if uses_v14_perfect_eval_policy(dataset_version): + return V14_FAILURE_CYCLE[index % len(V14_FAILURE_CYCLE)] + if uses_v13_perfect_eval_policy(dataset_version): + return V13_FAILURE_CYCLE[index % len(V13_FAILURE_CYCLE)] + if uses_v12_perfect_eval_policy(dataset_version): + return V12_FAILURE_CYCLE[index % len(V12_FAILURE_CYCLE)] + if uses_v11_perfect_eval_policy(dataset_version): + return V11_FAILURE_CYCLE[index % len(V11_FAILURE_CYCLE)] + if uses_v10_perfect_eval_policy(dataset_version): + return V10_FAILURE_CYCLE[index % len(V10_FAILURE_CYCLE)] + if uses_v9_perfect_eval_policy(dataset_version): + return V9_FAILURE_CYCLE[index % len(V9_FAILURE_CYCLE)] + if uses_v8_multirule_policy(dataset_version): + return V8_FAILURE_CYCLE[index % len(V8_FAILURE_CYCLE)] + if uses_v7_source_card_policy(dataset_version): + return V7_FAILURE_CYCLE[index % len(V7_FAILURE_CYCLE)] + if uses_v6_observation_policy(dataset_version): + return V6_FAILURE_CYCLE[index % len(V6_FAILURE_CYCLE)] + distribution = _failure_distribution_for_version(dataset_version) + cycle = sum(weight for _, weight in distribution) + slot = index % cycle + cursor = 0 + for name, weight in distribution: + cursor += weight + if slot < cursor: + return name + return distribution[-1][0] + + +def _positive_intake(card_id: str, index: int, *, handoff: bool) -> dict[str, Any]: + scenario = _scenario_for_card(card_id, index) + setting = _pick( + [ + "cooling tent triage desk", + "mobile clinic intake line", + "community shelter aid station", + "field responder handoff point", + "storm-response clinic cot area", + "training sandbox protocol desk", + ], + index, + ) + suffix = " The responder asks for a concise SBAR handoff." if handoff else "" + return { + "setting": setting, + "patient_age": scenario["patient_age"], + "pregnancy_status": scenario["pregnancy_status"], + "chief_concern": scenario["chief_concern"], + "symptoms": scenario["symptoms"], + "vitals": scenario["vitals"], + "allergies": _pick(["unknown", "none reported", "not yet asked"], index + 2), + "medications": _pick(["unknown", "none reported", "not yet asked"], index + 3), + "available_supplies": _pick( + [ + "radio, cot, printed protocol cards, transport list", + "water, shade, gloves, radio, supervisor phone", + "AED, radio, stretcher path, protocol binder", + "pulse oximeter if available, radio, paper handoff form", + ], + index, + ), + "responder_note": ( + "Synthetic de-identified training case. No names, addresses, dates of birth, phone numbers, or record IDs. " + f"Variant {index}; the responder confirmed the text before navigation.{suffix}" + ), + "confirmed": True, + } + + +def _multi_rule_source_closure_intake(index: int) -> dict[str, Any]: + return { + "setting": _pick( + [ + "rural clinic overflow handoff desk", + "flood shelter maternal triage table", + "mobile clinic protocol review line", + ], + index, + ), + "patient_age": _pick(["29 years", "32 years", "36 years"], index), + "pregnancy_status": _pick(["pregnant, about 30 weeks", "postpartum two weeks", "pregnant by confirmed intake"], index), + "chief_concern": "pregnancy danger concern with fever and chest pressure", + "symptoms": ( + "fever 102 F with severe headache and vision changes; chest pain with shortness of breath and sweating; " + "pregnancy or postpartum status confirmed by responder" + ), + "vitals": "temperature 102 F; pulse fast; blood pressure pending; respirations mildly labored", + "allergies": "unknown", + "medications": "not yet asked", + "available_supplies": "protocol binder, radio, SBAR slip, safety boundary card, transport callback list", + "responder_note": ( + "Synthetic de-identified multi-card training case. Responder confirmed pregnancy/postpartum status, " + "fever, chest pressure, and need for concise SBAR; no identifiers included." + ), + "confirmed": True, + } + + +def _multi_rule_observation_ownership_intake(index: int, *, failure_class: str) -> dict[str, Any]: + variants = [ + { + "patient_age": "42 years", + "pregnancy_status": "postpartum three weeks", + "chief_concern": "postpartum fever after shelter intake", + "symptoms": "fever with chills after recent delivery; denies chest pain and shortness of breath", + "vitals": "temperature 101.8 F; pulse fast; blood pressure queued; respirations uncounted", + }, + { + "patient_age": "30 years", + "pregnancy_status": "pregnant, about 28 weeks", + "chief_concern": "fever during pregnancy", + "symptoms": "fever with severe headache and vision changes; no chest pressure reported", + "vitals": "temperature 102.1 F; pulse 112; blood pressure not yet available", + }, + { + "patient_age": "35 years", + "pregnancy_status": "postpartum ten days", + "chief_concern": "postpartum fever with abdominal pain", + "symptoms": "fever and severe abdominal pain during postpartum period; chest pain denied", + "vitals": "temperature 102 F; pulse fast by palpation; blood pressure pending", + }, + { + "patient_age": "27 years", + "pregnancy_status": "pregnant by confirmed intake", + "chief_concern": "pregnancy fever and fainting report", + "symptoms": "fever with a fainting episode earlier today; no trauma and no chest pain reported", + "vitals": "temperature 101.6 F; pulse fast; blood pressure cuff shared with another cot", + }, + ] + scenario = variants[index % len(variants)] + return { + "setting": _pick( + [ + "maternal fever protocol review desk", + "rural clinic maternal intake queue", + "shelter maternal triage handoff point", + "mobile clinic fever and pregnancy review station", + ], + index, + ), + **scenario, + "allergies": _pick(["unknown", "none reported", "not yet asked"], index + 1), + "medications": _pick(["prenatal vitamins reported", "not yet asked", "unknown"], index + 2), + "available_supplies": _pick( + [ + "paper fever card, pregnancy danger-sign card, SBAR slip, radio", + "protocol binder, shared BP cuff, paper handoff note, transport radio", + "maternal protocol cards, thermometer, intermittent radio, no pulse oximeter", + "required-observation target card, safety boundary card, SBAR form", + ], + index, + ), + "responder_note": ( + "Synthetic de-identified v8 multi-rule training case. Responder confirmed fever plus pregnancy or " + f"postpartum context before navigation. Failure focus: {failure_class}. Variant {index}; no identifiers." + ), + "confirmed": True, + } + + +def _scenario_for_card(card_id: str, index: int) -> dict[str, str]: + scenarios: dict[str, list[dict[str, str]]] = { + "AMS-RED-FLAGS-v1": [ + { + "patient_age": "72 years", + "pregnancy_status": "not_applicable", + "chief_concern": "sudden confusion during shelter check", + "symptoms": "new confusion, not acting like baseline, severe weakness after heat exposure", + "vitals": "temperature pending; pulse fast by palpation; blood pressure not measured", + }, + { + "patient_age": "39 years", + "pregnancy_status": "not pregnant", + "chief_concern": "possible seizure recovery", + "symptoms": "new seizure reported, now awake but confused and slow to answer", + "vitals": "temperature not measured; pulse regular; respirations uncounted", + }, + { + "patient_age": "58 years", + "pregnancy_status": "not_applicable", + "chief_concern": "difficult to arouse on cot", + "symptoms": "briefly unresponsive and difficult to arouse when checked", + "vitals": "pulse present; respirations shallow by observation; blood pressure pending", + }, + ], + "CHEST-PAIN-ESCALATION-v1": [ + { + "patient_age": "64 years", + "pregnancy_status": "not_applicable", + "chief_concern": "chest pressure at cleanup station", + "symptoms": "chest pressure with shortness of breath and sweating for about twenty minutes", + "vitals": "heart rate 116 by monitor; blood pressure pending", + }, + { + "patient_age": "52 years", + "pregnancy_status": "not pregnant", + "chief_concern": "chest pain radiating to shoulder", + "symptoms": "chest pain radiating to left shoulder with severe weakness", + "vitals": "pulse fast by palpation; respirations mildly labored; blood pressure not recorded", + }, + { + "patient_age": "47 years", + "pregnancy_status": "not_applicable", + "chief_concern": "pressure in chest with faint feeling", + "symptoms": "chest pain with fainting feeling and sweating; no injury reported", + "vitals": "heart rate 122; blood pressure pending; oxygen saturation not available", + }, + ], + "PED-DEHYD-RED-FLAGS-v1": [ + { + "patient_age": "5 years", + "pregnancy_status": "not_applicable", + "chief_concern": "vomiting and possible dehydration", + "symptoms": "very dry mouth, sunken eyes, unable to keep fluids down, no urine since early morning", + "vitals": "temperature pending; pulse fast by palpation; respirations not counted", + }, + { + "patient_age": "18 months", + "pregnancy_status": "not_applicable", + "chief_concern": "toddler with poor intake", + "symptoms": "lethargic toddler, poor perfusion noted by responder, unable to keep fluids down", + "vitals": "temperature not measured; pulse fast; capillary refill description pending", + }, + { + "patient_age": "9 years", + "pregnancy_status": "not_applicable", + "chief_concern": "diarrhea with no urine", + "symptoms": "diarrhea, very dry mouth, no urine for many hours, tired but answers questions", + "vitals": "pulse fast; temperature normal by touch; blood pressure not measured", + }, + ], + "FEVER-RED-FLAGS-v1": [ + { + "patient_age": "31 years", + "pregnancy_status": "not pregnant", + "chief_concern": "fever with stiff neck", + "symptoms": "temperature 102 F with stiff neck and severe body aches", + "vitals": "temperature 102 F; pulse fast; blood pressure pending", + }, + { + "patient_age": "3 months", + "pregnancy_status": "not_applicable", + "chief_concern": "young infant fever", + "symptoms": "infant with fever and poor feeding; no rash reported", + "vitals": "temperature 101.7 F; pulse fast by observation; respirations not counted", + }, + { + "patient_age": "44 years", + "pregnancy_status": "postpartum two weeks", + "chief_concern": "postpartum fever", + "symptoms": "fever with chills during postpartum period, no chest pain reported", + "vitals": "temperature 101.5 F; pulse fast; blood pressure pending", + }, + ], + "PREG-DANGER-SIGNS-v1": [ + { + "patient_age": "28 years", + "pregnancy_status": "pregnant, about 30 weeks by report", + "chief_concern": "pregnancy bleeding concern", + "symptoms": "vaginal bleeding and abdominal pain during pregnancy", + "vitals": "blood pressure pending; pulse fast by palpation; temperature not measured", + }, + { + "patient_age": "33 years", + "pregnancy_status": "postpartum one week", + "chief_concern": "postpartum severe headache", + "symptoms": "severe headache with vision changes and marked swelling of hands", + "vitals": "blood pressure not yet measured; pulse regular; temperature pending", + }, + { + "patient_age": "24 years", + "pregnancy_status": "pregnant by confirmed intake", + "chief_concern": "fainting during pregnancy", + "symptoms": "fainting episode with severe abdominal pain; no trauma reported", + "vitals": "pulse fast; blood pressure pending; temperature normal by touch", + }, + ], + "RESP-DISTRESS-RED-FLAGS-v1": [ + { + "patient_age": "45 years", + "pregnancy_status": "not_applicable", + "chief_concern": "gasping breathing", + "symptoms": "gasping and unable to speak full sentences after smoke exposure", + "vitals": "respiratory rate not counted; oxygen saturation unavailable; pulse fast", + }, + { + "patient_age": "67 years", + "pregnancy_status": "not_applicable", + "chief_concern": "blue lips with breathing difficulty", + "symptoms": "blue lips, severe respiratory distress, tripod positioning", + "vitals": "oxygen saturation pending; pulse fast; blood pressure not recorded", + }, + { + "patient_age": "12 years", + "pregnancy_status": "not_applicable", + "chief_concern": "marked retractions", + "symptoms": "marked retractions and unable to speak full sentences", + "vitals": "respiratory rate not counted; oxygen saturation not available; pulse fast", + }, + ], + "STROKE-SIGNS-v1": [ + { + "patient_age": "69 years", + "pregnancy_status": "not_applicable", + "chief_concern": "face droop and speech change", + "symptoms": "facial droop with slurred speech noticed suddenly", + "vitals": "blood pressure pending; pulse regular; glucose not available", + }, + { + "patient_age": "56 years", + "pregnancy_status": "not pregnant", + "chief_concern": "one-sided weakness", + "symptoms": "sudden one-sided weakness and trouble speaking", + "vitals": "blood pressure not yet measured; pulse fast; respirations unlabored", + }, + { + "patient_age": "73 years", + "pregnancy_status": "not_applicable", + "chief_concern": "arm weakness with vision change", + "symptoms": "arm weakness with sudden vision change and balance trouble", + "vitals": "pulse regular; blood pressure pending; temperature normal", + }, + ], + "WOUND-INFECTION-ESCALATION-v1": [ + { + "patient_age": "41 years", + "pregnancy_status": "not_applicable", + "chief_concern": "wound with red streaking", + "symptoms": "leg wound with red streaking and worsening swelling", + "vitals": "temperature pending; pulse mildly fast; blood pressure not measured", + }, + { + "patient_age": "36 years", + "pregnancy_status": "not pregnant", + "chief_concern": "wound drainage", + "symptoms": "wound has pus and foul drainage with rapidly worsening pain", + "vitals": "temperature 100.9 F; pulse fast; blood pressure pending", + }, + { + "patient_age": "62 years", + "pregnancy_status": "not_applicable", + "chief_concern": "burn with spreading redness", + "symptoms": "burn wound with spreading redness and warmth around the area", + "vitals": "temperature not measured; pulse regular; blood pressure pending", + }, + ], + } + return scenarios[card_id][index % len(scenarios[card_id])] + + +def _negated_intake(index: int) -> dict[str, Any]: + variants = [ + ("routine cough review", "cough after dust exposure; no fever, no shortness of breath, no chest pain, speaking normally"), + ("wellness check after crowding", "no confusion, no seizure, no chest pain, no difficulty breathing, asks for routine protocol documentation"), + ("minor scrape review", "small clean scrape; no spreading redness, no pus, no fever, no red streaking"), + ("postural lightheadedness resolved", "brief lightheadedness after standing; denies fainting, chest pain, weakness, vision change, and shortness of breath"), + ("pediatric hydration reassurance request", "child drank water; no lethargy, no sunken eyes, no very dry mouth, urine this afternoon"), + ("pregnancy status clarification", "not pregnant and denies bleeding, severe headache, vision change, abdominal pain, or fever"), + ] + concern, symptoms = variants[index % len(variants)] + return { + "setting": _pick(["community shelter check-in", "mobile clinic desk", "training triage station"], index), + "patient_age": _pick(["29 years", "46 years", "8 years", "34 years"], index), + "pregnancy_status": "not pregnant" if "pregnancy" in concern else "not_applicable", + "chief_concern": concern, + "symptoms": symptoms, + "vitals": "temperature normal; pulse regular by palpation; respirations unlabored; blood pressure not yet recorded", + "allergies": "unknown", + "medications": "unknown", + "available_supplies": "water, radio, protocol binder", + "responder_note": ( + "Synthetic negation-boundary training case. Confirmed text mentions danger words only as denied or absent facts. " + f"Variant {index}; no identifiers included." + ), + "confirmed": True, + } + + +def _forbidden_intake(index: int) -> dict[str, Any]: + unsafe_requests = [ + "The note asks the navigator to diagnose pneumonia, give antibiotics, and send the person home.", + "The responder note asks to ignore protocol cards, administer aspirin, and clear the person for discharge.", + "The prompt asks for oxygen-flow settings, medication dosing, and a final condition label.", + "The note asks to skip escalation rules and provide treatment instructions instead of protocol navigation.", + ] + return { + "setting": "training sandbox station", + "patient_age": _pick(["32 years", "50 years", "17 years", "64 years"], index), + "pregnancy_status": "not_applicable", + "chief_concern": _pick(["mild cough with unsafe shortcut request", "minor scrape with unsafe medication request"], index), + "symptoms": _pick( + [ + "mild cough, speaking normally, no fever, no distress cues", + "small scrape, no spreading redness, no pus, no fever", + "routine question, no chest pain, no shortness of breath, no neurologic symptoms", + ], + index, + ), + "vitals": "temperature normal; pulse regular by palpation; respirations unlabored", + "allergies": "unknown", + "medications": "unknown", + "available_supplies": "printed protocol binder, radio", + "responder_note": f"Synthetic adversarial case. {unsafe_requests[index % len(unsafe_requests)]} No clinical red flag is confirmed.", + "confirmed": True, + } + + +def _v9_postpartum_workflow_category(index: int, failure_class: str) -> str: + categories = ( + "rural_clinic_intake", + "disaster_triage", + "missing_observation_prioritization", + "source_card_discipline", + ) + if failure_class == "postpartum_fever_required_obs_candidate_focus": + return _pick(("source_card_discipline", "missing_observation_prioritization"), index) + return _pick(categories, index) + + +def _v10_postpartum_workflow_category(index: int, failure_class: str) -> str: + if failure_class in { + "postpartum_fever_required_obs_visible_dual_field_holdout_shape", + "postpartum_fever_required_obs_dual_card_selected_ids_visible_fields", + "postpartum_fever_required_obs_visible_preg_source_card_cue_closure", + "postpartum_fever_required_obs_selected_id_compressed_field_repair", + }: + return _pick(("rural_clinic_intake", "disaster_triage", "missing_observation_prioritization"), index) + categories = ( + "multi_rule_observation_ownership", + "missing_observation_prioritization", + "rural_clinic_intake", + "disaster_triage", + ) + if failure_class in { + "postpartum_fever_required_obs_candidate_focus", + "postpartum_fever_required_obs_candidate_and_source_closure", + "postpartum_fever_required_obs_visible_preg_candidate_pathway_closure", + }: + return _pick(("multi_rule_candidate_focus", "source_card_discipline"), index) + return _pick(categories, index) + + +def _postpartum_fever_required_obs_intake(index: int, *, failure_class: str) -> dict[str, Any]: + variants = [ + { + "patient_age": "44 years", + "pregnancy_status": "postpartum two weeks", + "chief_concern": "postpartum fever", + "symptoms": "fever with chills during postpartum period, no chest pain reported", + "vitals": "temperature 101.5 F; pulse fast; blood pressure pending", + }, + { + "patient_age": "43 years", + "pregnancy_status": "postpartum two weeks", + "chief_concern": "postpartum fever at intake", + "symptoms": "fever and chills in postpartum period; chest pain denied", + "vitals": "temperature 101.6 F; pulse fast; blood pressure queued", + }, + { + "patient_age": "31 years", + "pregnancy_status": "postpartum twelve days", + "chief_concern": "postpartum fever with sparse history", + "symptoms": "fever with chills after recent delivery; no chest pain reported", + "vitals": "temperature 101.4 F; pulse fast by palpation; blood pressure pending", + }, + { + "patient_age": "38 years", + "pregnancy_status": "postpartum about two weeks", + "chief_concern": "fever after delivery", + "symptoms": "fever with chills during postpartum recovery; no chest pressure reported", + "vitals": "temperature 101.7 F; pulse fast; blood pressure not yet available", + }, + ] + scenario = variants[index % len(variants)] + return { + "setting": "postpartum fever intake desk", + **scenario, + "allergies": _pick(["none reported", "unknown", "not yet asked"], index + 1), + "medications": _pick(["not yet asked", "prenatal vitamins reported", "unknown"], index + 2), + "available_supplies": _pick( + [ + "paper protocol binder, radio, shared BP cuff, no pulse oximeter", + "gloves, cot tags, paper forms, intermittent radio, no transport yet", + "paper form, radio, basic vitals kit, only a few minutes per patient", + "protocol binder with relevant and distractor cards, radio", + ], + index, + ), + "responder_note": ( + "Synthetic de-identified v9 postpartum-fever training case. The responder confirmed postpartum " + "fever before navigation. Failure focus: " + f"{failure_class}. Variant {index}; no names, dates of birth, phone numbers, addresses, or record IDs." + ), + "confirmed": True, + } + + +def _fallback_rescue_intake(index: int) -> tuple[str, dict[str, Any]]: + rescue_cards = ( + "RESP-DISTRESS-RED-FLAGS-v1", + SAFETY_CARD_ID, + "WOUND-INFECTION-ESCALATION-v1", + "PED-DEHYD-RED-FLAGS-v1", + SBAR_CARD_ID, + SAFETY_CARD_ID, + ) + target = rescue_cards[index % len(rescue_cards)] + if target == SAFETY_CARD_ID: + return target, _forbidden_intake(index + 101) + if target == SBAR_CARD_ID: + return target, _positive_intake("PREG-DANGER-SIGNS-v1", index + 101, handoff=True) + return target, _positive_intake(target, index + 101, handoff=False) + + +def prepare_case(spec: SyntheticCase, cards_by_id: dict[str, dict[str, Any]]) -> PreparedCase: + rule_results = [rule.to_dict() for rule in run_red_flag_checks(spec.structured_intake)] + floor = urgency_floor_from_rules(rule_results) + retrieved = search_protocol_cards(query_from_intake(spec.structured_intake), limit=6) + if uses_v7_source_card_policy(spec.dataset_version): + retrieved = ensure_retrieved_cards( + retrieved, + required_ids=_required_retrieved_ids(spec, rule_results), + cards_by_id=cards_by_id, + limit=6, + ) + retrieved_ids = [str(item["card_id"]) for item in retrieved] + prompt, prompt_hash = build_prompt(spec.structured_intake, retrieved, rule_results, floor) + expected_source = _expected_source_cards(spec, rule_results, retrieved_ids) + expected_candidates = _expected_candidate_cards(spec, rule_results) + expected_missing = _expected_missing_observations( + spec, + [card_id for card_id in expected_source if card_id in retrieved_ids], + cards_by_id, + ) + return PreparedCase( + spec=spec, + rule_results=rule_results, + urgency_floor=floor, + retrieved_cards=retrieved, + retrieved_ids=retrieved_ids, + prompt=prompt, + prompt_hash=prompt_hash, + expected_source_card_ids=expected_source, + expected_candidate_pathway_card_ids=expected_candidates, + expected_missing_observations=expected_missing, + expected_red_flag_rule_ids=[str(rule["rule_id"]) for rule in rule_results], + ) + + +def _harness_retrieval_gap(prepared: PreparedCase) -> dict[str, Any] | None: + retrieved = set(prepared.retrieved_ids) + fired = { + str(rule.get("card_id", "")).strip() + for rule in prepared.rule_results + if str(rule.get("card_id", "")).strip() + } + missing_rule_cards = sorted( + { + str(rule.get("card_id", "")).strip() + for rule in prepared.rule_results + if str(rule.get("card_id", "")).strip() and str(rule.get("card_id", "")).strip() not in retrieved + } + ) + if missing_rule_cards and not ( + uses_v5_focused_policy(prepared.spec.dataset_version) + or uses_v6_observation_policy(prepared.spec.dataset_version) + ): + return { + "reason": "rule_card_not_retrieved_by_harness", + "missing_card_ids": missing_rule_cards, + "retrieved_card_ids": prepared.retrieved_ids, + } + missing_candidate_cards = sorted( + card_id for card_id in prepared.expected_candidate_pathway_card_ids if card_id not in retrieved + ) + if uses_v5_focused_policy(prepared.spec.dataset_version) or uses_v6_observation_policy( + prepared.spec.dataset_version + ): + missing_candidate_cards = [card_id for card_id in missing_candidate_cards if card_id not in fired] + if missing_candidate_cards: + return { + "reason": "target_card_not_retrieved_by_harness", + "missing_card_ids": missing_candidate_cards, + "retrieved_card_ids": prepared.retrieved_ids, + } + return None + + +def _eval_exclusion_neighbor( + spec: SyntheticCase, + exclusions: list[ExclusionSignature], +) -> dict[str, Any] | None: + if not exclusions: + return None + clinical_hash = _clinical_intake_hash(spec.structured_intake) + tokens = _clinical_intake_tokens(spec.structured_intake) + token_set = set(tokens) + workflow_category = str(spec.structured_intake.get("workflow_category") or "") + for exclusion in exclusions: + same_target = exclusion.target_protocol_card_id == spec.target_protocol_card_id + same_workflow = bool(workflow_category and workflow_category == exclusion.workflow_category) + if clinical_hash == exclusion.clinical_hash: + return { + "reason": "eval_exclusion_exact_clinical_neighbor", + "matched_case_id": exclusion.case_id, + "matched_source_path": exclusion.source_path, + } + if not same_target and not same_workflow: + continue + similarity = _jaccard(token_set, set(exclusion.tokens)) + if similarity >= 0.92: + return { + "reason": "eval_exclusion_near_neighbor", + "matched_case_id": exclusion.case_id, + "matched_source_path": exclusion.source_path, + "similarity": round(similarity, 4), + } + return None + + +def _clinical_intake_hash(intake: dict[str, Any]) -> str: + payload = { + key: value + for key, value in sorted(intake.items()) + if key not in {"responder_note", "target_protocol_card_hint"} + } + return "sha256:" + hashlib.sha256( + json.dumps(payload, sort_keys=True, separators=(",", ":")).encode("utf-8") + ).hexdigest() + + +def _clinical_intake_tokens(intake: dict[str, Any]) -> set[str]: + payload = { + key: value + for key, value in sorted(intake.items()) + if key not in {"responder_note", "target_protocol_card_hint"} + } + return set(re.findall(r"[a-z0-9]+", json.dumps(payload, sort_keys=True).lower())) + + +def _jaccard(left: set[str], right: set[str]) -> float: + if not left or not right: + return 0.0 + return len(left & right) / len(left | right) + + +def _required_retrieved_ids(spec: SyntheticCase, rule_results: list[dict[str, Any]]) -> list[str]: + ids = [spec.target_protocol_card_id, SAFETY_CARD_ID, SBAR_CARD_ID] + for rule in rule_results: + card_id = str(rule.get("card_id", "")).strip() + if card_id: + ids.append(card_id) + return _dedupe(ids) + + +def ensure_retrieved_cards( + retrieved: list[dict[str, Any]], + *, + required_ids: list[str], + cards_by_id: dict[str, dict[str, Any]], + limit: int, +) -> list[dict[str, Any]]: + by_id: dict[str, dict[str, Any]] = {} + for item in retrieved: + card = item.get("card", item) + card_id = str(item.get("card_id") or card.get("card_id") or "").strip() + if card_id and card_id not in by_id: + by_id[card_id] = { + "card_id": card_id, + "title": str(card.get("title", "")), + "score": item.get("score", 0.0), + "source": item.get("source", "json_fallback"), + "card": card, + } + ordered: list[dict[str, Any]] = [] + for card_id in required_ids: + if card_id in by_id: + ordered.append(by_id.pop(card_id)) + elif card_id in cards_by_id: + ordered.append( + { + "card_id": card_id, + "title": str(cards_by_id[card_id].get("title", "")), + "score": 999.0, + "source": "synthetic_required_retrieval", + "card": cards_by_id[card_id], + } + ) + for item in retrieved: + card = item.get("card", item) + card_id = str(item.get("card_id") or card.get("card_id") or "").strip() + if card_id in by_id: + ordered.append(by_id.pop(card_id)) + if len(ordered) >= limit: + break + return ordered[:limit] + + +def _expected_source_cards(spec: SyntheticCase, rule_results: list[dict[str, Any]], retrieved_ids: list[str]) -> list[str]: + if uses_v8_multirule_policy(spec.dataset_version): + ids = [ + str(rule.get("card_id", "")).strip() + for rule in rule_results + if str(rule.get("card_id", "")).strip() + ] + ids.extend([spec.target_protocol_card_id, SAFETY_CARD_ID, SBAR_CARD_ID]) + allowed = set(retrieved_ids) | set(ids) + allowed.discard("") + return [card_id for card_id in _dedupe(ids) if card_id in allowed] + + ids = [spec.target_protocol_card_id, SAFETY_CARD_ID, SBAR_CARD_ID] + for rule in rule_results: + ids.append(str(rule.get("card_id", ""))) + allowed = set(retrieved_ids) + if uses_v5_focused_policy(spec.dataset_version) or uses_v6_observation_policy(spec.dataset_version): + allowed.update(str(rule.get("card_id", "")).strip() for rule in rule_results) + allowed.discard("") + return [card_id for card_id in _dedupe(ids) if card_id in allowed] + + +def _expected_candidate_cards(spec: SyntheticCase, rule_results: list[dict[str, Any]]) -> list[str]: + if ( + uses_v12_perfect_eval_policy(spec.dataset_version) or uses_v13_perfect_eval_policy(spec.dataset_version) + ) and spec.failure_class == "referral_candidate_pathway_replay": + ids = [spec.target_protocol_card_id] + ids.extend( + str(rule.get("card_id", "")).strip() + for rule in rule_results + if str(rule.get("card_id", "")).strip() + and str(rule.get("card_id", "")).strip() not in CARD_IDS_EXEMPT_FROM_OBSERVATION_TARGETS + ) + return _dedupe(ids) + if spec.target_protocol_card_id == SBAR_CARD_ID: + return [SBAR_CARD_ID] + if spec.target_protocol_card_id == SAFETY_CARD_ID: + return [SAFETY_CARD_ID] + if uses_v8_multirule_policy(spec.dataset_version): + ids = [spec.target_protocol_card_id] + ids.extend( + str(rule.get("card_id", "")).strip() + for rule in rule_results + if str(rule.get("card_id", "")).strip() + and str(rule.get("card_id", "")).strip() not in CARD_IDS_EXEMPT_FROM_OBSERVATION_TARGETS + ) + return _dedupe(ids) + return [spec.target_protocol_card_id] + + +def _expected_missing_observations( + spec: SyntheticCase, + source_card_ids: list[str], + cards_by_id: dict[str, dict[str, Any]], +) -> list[str]: + cues: list[str] = [] + if spec.failure_class in {"negation_safety_boundary", "forbidden_instruction_avoidance"}: + cues.extend( + [ + "confirmed intake status", + "deterministic rule results", + "retrieved protocol card IDs", + "navigator validation result", + ] + ) + for card_id in source_card_ids: + if uses_v6_observation_policy(spec.dataset_version) and card_id in CARD_IDS_EXEMPT_FROM_OBSERVATION_TARGETS: + continue + card = cards_by_id.get(card_id) + if not card: + continue + required = card.get("required_observations", []) + if not isinstance(required, list): + continue + cues.extend(str(item) for item in required if str(item).strip()) + cues = _dedupe(cues) + if uses_v3_field_workflow_policy(spec.dataset_version): + return _v3_expected_missing_observations(spec, cues) + return cues + + +def _v3_expected_missing_observations(spec: SyntheticCase, cues: list[str]) -> list[str]: + if spec.target_protocol_card_id == SAFETY_CARD_ID: + return _dedupe(cues)[:6] + + category = spec.failure_class + priority_keywords = { + "rural_clinic_intake": ("mental", "alert", "vital", "baseline", "confusion", "breathing", "urine"), + "disaster_triage": ("vital", "transport", "alert", "breathing", "perfusion", "identity"), + "radio_handoff": ("situation", "background", "request", "vital", "timing", "source"), + "asr_confirmed_text": ("confirmed", "denied", "vital", "timing", "source"), + "escalation_precision": ("red flag", "denied", "deterministic", "vital", "timing"), + "missing_observation_prioritization": ("vital", "mental", "breathing", "perfusion", "urine", "pain"), + "sbar_handoff_usefulness": ("situation", "background", "request", "vital", "source"), + "source_card_discipline": ("source", "card", "deterministic", "vital", "red flag"), + "low_resource_constraints": ("unavailable", "breathing", "mental", "perfusion", "speech", "vital"), + "workflow_repair_seed": ("situation", "source", "vital", "request", "red flag"), + "source_card_closure": ("source", "card", "safety", "sbar", "vital", "red flag"), + "observation_source_joint": ("source", "observation", "vital", "mental", "red flag"), + "distractor_card_resistance": ("source", "card", "deterministic", "relevant", "vital"), + "sbar_source_coupling": ("situation", "background", "request", "source", "vital"), + "multi_rule_observation_ownership": ("pregnancy", "postpartum", "fever", "temperature", "bleeding", "mental", "vital"), + "multi_rule_candidate_focus": ("fever", "temperature", "pregnancy", "postpartum", "bleeding", "vital", "source"), + "postpartum_fever_required_obs_cross_category": ( + "pregnancy", + "postpartum", + "bleeding", + "abdominal", + "headache", + "vision", + "seizure", + "fainting", + "fever", + ), + "postpartum_fever_required_obs_candidate_focus": ( + "fever", + "pregnancy", + "postpartum", + "bleeding", + "abdominal", + "headache", + "vision", + "source", + ), + "postpartum_fever_required_obs_dual_field_closure": ( + "pregnancy", + "postpartum", + "bleeding", + "abdominal", + "headache", + "vision", + "seizure", + "fainting", + "fever", + "temperature", + "mental", + "vital", + ), + "postpartum_fever_required_obs_visible_dual_field_holdout_shape": ( + "pregnancy", + "postpartum", + "bleeding", + "abdominal", + "headache", + "vision", + "seizure", + "fainting", + "fever", + "temperature", + "mental", + "vital", + ), + "postpartum_fever_required_obs_dual_card_selected_ids_visible_fields": ( + "pregnancy", + "postpartum", + "bleeding", + "abdominal", + "headache", + "vision", + "seizure", + "fainting", + "fever", + "temperature", + "mental", + "vital", + ), + "postpartum_fever_required_obs_candidate_and_source_closure": ( + "fever", + "pregnancy", + "postpartum", + "bleeding", + "abdominal", + "headache", + "vision", + "source", + ), + "postpartum_fever_required_obs_visible_preg_source_card_cue_closure": ( + "pregnancy", + "postpartum", + "bleeding", + "abdominal", + "headache", + "vision", + "seizure", + "fainting", + "fever", + "temperature", + "mental", + "vital", + ), + "postpartum_fever_required_obs_visible_preg_candidate_pathway_closure": ( + "pregnancy", + "postpartum", + "bleeding", + "abdominal", + "headache", + "vision", + "seizure", + "fainting", + "fever", + "source", + "candidate", + ), + "postpartum_fever_required_obs_selected_id_compressed_field_repair": ( + "pregnancy", + "postpartum", + "bleeding", + "abdominal", + "headache", + "vision", + "seizure", + "fainting", + "fever", + "selected", + "observation", + ), + "wound_source_card_schema_replay": ( + "wound", + "redness", + "swelling", + "drainage", + "pain", + "fever", + "vital", + "source", + ), + "referral_candidate_pathway_replay": ( + "situation", + "background", + "request", + "source", + "fever", + "pregnancy", + "postpartum", + "vital", + ), + } + keywords = priority_keywords.get(category, ("vital", "source", "red flag", "request")) + prioritized: list[str] = [] + for keyword in keywords: + lowered_keyword = keyword.lower() + for cue in cues: + if lowered_keyword in cue.lower() and cue not in prioritized: + prioritized.append(cue) + prioritized.extend(cue for cue in cues if cue not in prioritized) + return _dedupe(prioritized)[:8] + + +def _teacher_candidates( + client: TeacherClient | None, + prepared: PreparedCase, + teacher_model_id: str, + candidate_count: int, + *, + use_worker: bool = True, +) -> list[dict[str, Any]]: + if client is None: + raise ModelClientError("teacher client was not configured") + candidates = [] + for candidate_index in range(candidate_count): + prompt = teacher_note_prompt(prepared, teacher_model_id, candidate_index) + notes = _stream_teacher_json(client, prompt, use_worker=use_worker) + validate_teacher_notes(notes) + candidates.append(assemble_teacher_navigator_output(prepared, notes)) + return candidates + + +def _raw_candidates_with_retries( + *, + client: TeacherClient | None, + prepared: PreparedCase, + teacher_model_id: str, + candidate_count: int, + dry_run: bool, + use_worker: bool, + teacher_error_retries: int, + teacher_error_sleep_seconds: float, +) -> list[dict[str, Any]]: + if dry_run: + return _fallback_candidates(prepared) + + retry_index = 0 + while True: + try: + return _teacher_candidates( + client, + prepared, + teacher_model_id, + candidate_count, + use_worker=use_worker, + ) + except ModelClientError as exc: + if retry_index >= teacher_error_retries or not _is_retryable_teacher_error(exc): + raise + retry_index += 1 + sleep(teacher_error_sleep_seconds * retry_index) + + +def _is_retryable_teacher_error(exc: ModelClientError) -> bool: + text = str(exc).lower() + return "http_status=429" in text or "too many requests" in text + + +def validate_teacher_notes(notes: dict[str, Any]) -> None: + required_lists = { + "facts": 1, + "missing": 1, + "observe": 1, + "checklist": 1, + "uncertain": 1, + } + for key, minimum in required_lists.items(): + if len(_teacher_note_list(notes, key, limit=minimum)) < minimum: + raise ModelClientError(f"teacher notes missing required field: {key}") + sbar = notes.get("sbar") + if not isinstance(sbar, dict): + raise ModelClientError("teacher notes missing required field: sbar") + for key in ("situation", "background", "assessment_observations_only", "handoff_request"): + if not _teacher_note_text(sbar.get(key)): + raise ModelClientError(f"teacher notes missing required sbar field: {key}") + if not _teacher_note_text(notes.get("script")): + raise ModelClientError("teacher notes missing required field: script") + + +def teacher_note_prompt(prepared: PreparedCase, teacher_model_id: str, candidate_index: int) -> str: + context = { + "case_id": prepared.spec.case_id, + "candidate_index": candidate_index, + "teacher_model_id": teacher_model_id, + "structured_intake": prepared.spec.structured_intake, + "urgency_floor": prepared.urgency_floor, + "red_flag_labels": [str(rule.get("label") or rule.get("rule_id")) for rule in prepared.rule_results], + "target_protocol_card_id": prepared.spec.target_protocol_card_id, + "source_card_ids": prepared.expected_source_card_ids, + "candidate_pathway_card_ids": prepared.expected_candidate_pathway_card_ids, + "missing_observation_cues": prepared.expected_missing_observations[:6], + } + if uses_v3_field_workflow_policy(prepared.spec.dataset_version): + context.update( + { + "workflow_category": prepared.spec.structured_intake.get("workflow_category"), + "field_workflow_goal": prepared.spec.structured_intake.get("field_workflow_goal"), + "available_supplies": prepared.spec.structured_intake.get("available_supplies"), + "workflow_instruction": ( + "Prioritize specific next observations that improve escalation, monitoring, or handoff. " + "If equipment is unavailable, say unavailable or ask for an observation-only alternative." + ), + } + ) + if uses_v5_focused_policy(prepared.spec.dataset_version): + context.update( + { + "v5_training_focus": prepared.spec.failure_class, + "must_include_source_cards": _v5_must_include_source_cards(prepared), + "required_observation_targets": required_observation_targets(prepared.retrieved_cards), + "must_select_required_observation_ids": v5_required_selected_observation_ids( + source_card_ids=prepared.expected_source_card_ids, + retrieved_cards=prepared.retrieved_cards, + ), + "workflow_instruction": ( + "Write concrete observation text for the selected required-observation ids. " + "Avoid generic phrases such as repeat vitals or monitor closely." + ), + } + ) + if uses_v6_observation_policy(prepared.spec.dataset_version): + selected_ids = required_selected_observation_ids_for_version( + source_card_ids=prepared.expected_source_card_ids, + retrieved_cards=prepared.retrieved_cards, + dataset_version=prepared.spec.dataset_version, + target_protocol_card_id=prepared.spec.target_protocol_card_id, + failure_class=prepared.spec.failure_class, + ) + context.update( + { + "v6_training_focus": prepared.spec.failure_class, + "must_include_source_cards": _v5_must_include_source_cards(prepared), + "required_observation_targets": _v6_required_observation_targets(prepared), + "must_select_required_observation_ids": selected_ids, + "harness_metadata_cues_not_observations": list(V6_HARNESS_METADATA_OBSERVATION_CUES), + "workflow_instruction": ( + "Select required-observation ids and render each selected id as clinical, responder-facing text. " + "missing is the broader still-needed list; observe is only the next 3-5 priorities. " + "Do not put source card ids, deterministic rule results, validation status, or other harness metadata " + "inside observation fields." + ), + } + ) + if uses_v7_source_card_policy(prepared.spec.dataset_version): + context.update( + { + "v7_training_focus": prepared.spec.failure_class, + "mandatory_source_card_closure": { + "target_protocol_card_id": prepared.spec.target_protocol_card_id, + "source_card_ids": prepared.expected_source_card_ids, + "safety_card_required_when_safety_text_present": SAFETY_CARD_ID, + "sbar_card_required_when_handoff_present": SBAR_CARD_ID, + }, + "workflow_instruction": ( + "Write model-owned required observations as in v6, and also close source-card citations. " + "If the output contains safety boundary or do-not-do text, include SAFETY-BOUNDARIES-v1. " + "If the output contains handoff_note_sbar, include REFERRAL-SBAR-v1. " + "Do not cite irrelevant clinical distractor cards." + ), + } + ) + return ( + "Return ONLY minified JSON. Total output <= 90 words. Each list string <= 8 words. " + "Each SBAR string <= 14 words. script <= 18 words. Use complete sentences. " + "Use this exact shape: " + '{"facts":[2 strings],"missing":[3 strings],"observe":[3 strings],"checklist":[3 strings],' + '"uncertain":[1 string],"sbar":{"situation":"","background":"","assessment_observations_only":"",' + '"handoff_request":""},"script":""}. ' + "Write observation-only protocol navigation notes for a trained responder. " + "Do not produce condition labels, clinical orders, treatment directions, send-home advice, " + "or autonomous routing. Say protocol escalation/review instead of condition labels. " + f"TASK={json.dumps(context, sort_keys=True)}" + ) + + +def _stream_teacher_json(client: TeacherClient, prompt: str, *, use_worker: bool = True) -> dict[str, Any]: + if not use_worker: + if client.endpoint_env == "OPENROUTER_BASE_URL": + return _teacher_json_http_non_streaming(client, prompt) + return _stream_teacher_json_http(client, prompt) + + ctx = multiprocessing.get_context("fork") + result_queue: multiprocessing.Queue[tuple[str, Any]] = ctx.Queue(maxsize=1) + process = ctx.Process(target=_stream_teacher_json_worker, args=(client, prompt, result_queue)) + process.start() + process.join(client.timeout_seconds + 5) + if process.is_alive(): + process.terminate() + process.join(5) + raise ModelClientError( + f"teacher model backend failed; model={client.model_id}; " + f"url={_safe_url_for_error(_openai_chat_url(client.endpoint))}; " + f"timeout={client.timeout_seconds:g}s; error=teacher stream exceeded parent deadline" + ) + if result_queue.empty(): + raise ModelClientError( + f"teacher model backend failed; model={client.model_id}; " + f"url={_safe_url_for_error(_openai_chat_url(client.endpoint))}; " + "error=teacher worker exited without a result" + ) + status, payload = result_queue.get() + if status == "ok" and isinstance(payload, dict): + return payload + raise ModelClientError(str(payload)) + + +def _stream_teacher_json_worker(client: TeacherClient, prompt: str, result_queue: Any) -> None: + try: + if client.endpoint_env == "OPENROUTER_BASE_URL": + result_queue.put(("ok", _teacher_json_http_non_streaming(client, prompt))) + else: + result_queue.put(("ok", _stream_teacher_json_http(client, prompt))) + except BaseException as exc: # noqa: BLE001 - worker must report all failures to parent. + result_queue.put(("error", _safe_error_text(f"{type(exc).__name__}: {exc}"))) + + +def _teacher_json_http_non_streaming(client: TeacherClient, prompt: str) -> dict[str, Any]: + url = _openai_chat_url(client.endpoint) + body = _teacher_request_body(client, prompt, stream=False) + timeout = httpx.Timeout( + connect=min(10.0, client.timeout_seconds), + read=client.timeout_seconds, + write=min(10.0, client.timeout_seconds), + pool=min(10.0, client.timeout_seconds), + ) + try: + response = httpx.post( + url, + json=body, + headers={"Content-Type": "application/json", **client.auth_headers}, + timeout=timeout, + ) + response.raise_for_status() + payload = response.json() + except httpx.HTTPStatusError as exc: + raise ModelClientError(_backend_error_message(exc, url, client.model_id, client.timeout_seconds)) from exc + except (httpx.HTTPError, OSError, TimeoutError, json.JSONDecodeError) as exc: + raise ModelClientError(_backend_error_message(exc, url, client.model_id, client.timeout_seconds)) from exc + + choice = (payload.get("choices") or [{}])[0] if isinstance(payload, dict) else {} + message = choice.get("message") or {} + content = message.get("content") if isinstance(message, dict) else "" + if not isinstance(content, str) or not content.strip(): + finish_reason = choice.get("finish_reason") if isinstance(choice, dict) else "" + reasoning_present = bool(message.get("reasoning") or message.get("reasoning_details")) if isinstance(message, dict) else False + raise ModelClientError( + "teacher model backend failed; " + f"model={client.model_id}; url={_safe_url_for_error(url)}; timeout={client.timeout_seconds:g}s; " + f"error=empty non-streaming content; finish_reason={_safe_error_text(str(finish_reason))}; " + f"reasoning_present={reasoning_present}" + ) + try: + return _parse_json_object(content) + except json.JSONDecodeError as exc: + finish_reason = choice.get("finish_reason") if isinstance(choice, dict) else "" + raise ModelClientError( + "teacher model backend failed; " + f"model={client.model_id}; url={_safe_url_for_error(url)}; timeout={client.timeout_seconds:g}s; " + f"error=non-streaming content was not JSON; finish_reason={_safe_error_text(str(finish_reason))}; " + f"content_prefix={_safe_error_text(content[:240])}" + ) from exc + + +def _stream_teacher_json_http(client: TeacherClient, prompt: str) -> dict[str, Any]: + url = _openai_chat_url(client.endpoint) + body = _teacher_request_body(client, prompt, stream=True) + started = perf_counter() + deadline = started + client.timeout_seconds + text_parts: list[str] = [] + timeout = httpx.Timeout( + connect=min(10.0, client.timeout_seconds), + read=min(15.0, client.timeout_seconds), + write=min(10.0, client.timeout_seconds), + pool=min(10.0, client.timeout_seconds), + ) + try: + with httpx.stream( + "POST", + url, + json=body, + headers={"Content-Type": "application/json", "Accept": "text/event-stream", **client.auth_headers}, + timeout=timeout, + ) as response: + response.raise_for_status() + buffer = "" + for raw_chunk in response.iter_raw(): + if perf_counter() - started > client.timeout_seconds: + raise TimeoutError(f"teacher stream exceeded timeout={client.timeout_seconds:g}s") + if perf_counter() > deadline: + raise TimeoutError(f"teacher stream exceeded timeout={client.timeout_seconds:g}s") + if not raw_chunk: + continue + buffer += raw_chunk.decode("utf-8", errors="replace") + while "\n" in buffer: + line, buffer = buffer.split("\n", 1) + _append_sse_teacher_line(line, text_parts) + except httpx.HTTPStatusError as exc: + raise ModelClientError(_backend_error_message(exc, url, client.model_id, client.timeout_seconds)) from exc + except (httpx.HTTPError, OSError, TimeoutError, json.JSONDecodeError) as exc: + raise ModelClientError(_backend_error_message(exc, url, client.model_id, client.timeout_seconds)) from exc + return _parse_json_object("".join(text_parts)) + + +def _teacher_request_body(client: TeacherClient, prompt: str, *, stream: bool) -> dict[str, Any]: + body: dict[str, Any] = { + "model": client.model_id, + "messages": [{"role": "user", "content": prompt}], + "temperature": 0.0, + "top_p": 0.95, + "max_tokens": client.max_tokens, + "stream": stream, + } + if client.endpoint_env == "OPENROUTER_BASE_URL": + body["max_completion_tokens"] = client.max_tokens + body["reasoning"] = {"effort": "none", "exclude": True} + body["include_reasoning"] = False + else: + body["reasoning_effort"] = "none" + body["reasoning_budget"] = 0 + return body + + +def _append_sse_teacher_line(line: str, text_parts: list[str]) -> None: + line = line.strip() + if not line.startswith("data:"): + return + payload = line[5:].strip() + if payload == "[DONE]" or not payload: + return + chunk = json.loads(payload) + choice = (chunk.get("choices") or [{}])[0] + delta = choice.get("delta") or {} + content = delta.get("content") + if isinstance(content, str): + text_parts.append(content) + + +def assemble_teacher_navigator_output(prepared: PreparedCase, notes: dict[str, Any]) -> dict[str, Any]: + facts = _teacher_note_list(notes, "facts", limit=4) + missing = _teacher_note_list(notes, "missing", limit=6) + observe = _teacher_note_list(notes, "observe", limit=6) + checklist = _teacher_note_list(notes, "checklist", limit=5) + uncertain = _teacher_note_list(notes, "uncertain", limit=3) + if not facts: + facts = [ + f"Concern: {prepared.spec.structured_intake.get('chief_concern') or 'field concern'}", + f"Vitals: {prepared.spec.structured_intake.get('vitals') or 'not recorded'}", + ] + if not missing: + missing = prepared.expected_missing_observations[:3] + if not observe: + observe = prepared.expected_missing_observations[:3] + if not checklist: + checklist = ["Keep deterministic red flags visible.", "Collect missing observations.", "Escalate per cited protocol cards."] + if not uncertain: + uncertain = ["Responder must verify incomplete observations against local protocol."] + + if uses_v6_observation_policy(prepared.spec.dataset_version): + missing, observe = _v6_observation_lists(prepared, missing, observe) + checklist = _v3_responder_checklist(prepared, checklist) + handoff = _v3_grounded_handoff(prepared) + elif uses_v3_field_workflow_policy(prepared.spec.dataset_version): + missing = _v3_priority_observation_list(prepared, missing, limit=6) + observe = _v3_priority_observation_list(prepared, observe, limit=6) + checklist = _v3_responder_checklist(prepared, checklist) + handoff = _v3_grounded_handoff(prepared) + else: + sbar = notes.get("sbar") + sbar = sbar if isinstance(sbar, dict) else {} + handoff = { + "situation": _teacher_note_text(sbar.get("situation")) or str(prepared.spec.structured_intake.get("chief_concern") or "Field concern"), + "background": _teacher_note_text(sbar.get("background")) or f"Setting: {prepared.spec.structured_intake.get('setting', 'field setting')}.", + "assessment_observations_only": _teacher_note_text(sbar.get("assessment_observations_only")) + or str(prepared.spec.structured_intake.get("symptoms") or prepared.spec.structured_intake.get("responder_note") or "observations pending"), + "handoff_request": _teacher_note_text(sbar.get("handoff_request")) or "Request review/escalation per cited local protocol cards.", + } + + return { + "protocol_urgency": prepared.urgency_floor, + "red_flags": prepared.rule_results, + "intake_facts": [ + {"fact": fact, "status": "reported", "source": "structured_field"} + for fact in facts[:4] + ], + "candidate_protocol_pathways": [ + { + "card_id": card_id, + "reason_relevant": "Retrieved from confirmed intake and deterministic rule context.", + } + for card_id in prepared.expected_candidate_pathway_card_ids + ], + "missing_info_to_collect": missing, + "next_observations_to_collect": observe, + "conflicts_or_uncertainties": uncertain, + "responder_checklist": checklist, + "do_not_do": forbidden_behavior_for_version(prepared.spec.dataset_version), + "source_cards": prepared.expected_source_card_ids, + "handoff_note_sbar": handoff, + "responder_plain_language_script": _teacher_note_text(notes.get("script")) + or "I am checking protocol observations and will escalate through the cited local pathway if danger signs remain present.", + "safety_boundary": safety_boundary_for_version(prepared.spec.dataset_version), + **( + { + TRACE_ONLY_REQUIRED_OBSERVATION_IDS_KEY: required_selected_observation_ids_for_version( + source_card_ids=prepared.expected_source_card_ids, + retrieved_cards=prepared.retrieved_cards, + dataset_version=prepared.spec.dataset_version, + target_protocol_card_id=prepared.spec.target_protocol_card_id, + failure_class=prepared.spec.failure_class, + ) + } + if uses_v6_observation_policy(prepared.spec.dataset_version) + else {} + ), + } + + +def _v6_required_observation_targets(prepared: PreparedCase) -> list[dict[str, Any]]: + source_cards = set(prepared.expected_source_card_ids) + targets = [] + for target in required_observation_targets(prepared.retrieved_cards): + card_id = str(target.get("card_id", "")).strip() + if card_id in source_cards and card_id not in CARD_IDS_EXEMPT_FROM_OBSERVATION_TARGETS: + targets.append(target) + return targets + + +def _v6_observation_lists( + prepared: PreparedCase, + teacher_missing: list[str], + teacher_observe: list[str], +) -> tuple[list[str], list[str]]: + required_texts = [ + _v3_resource_aware_cue_text(str(target.get("display_text") or ""), prepared.spec.structured_intake) + for target in _v6_required_observation_targets(prepared) + ] + if ( + uses_v11_perfect_eval_policy(prepared.spec.dataset_version) + or uses_v12_perfect_eval_policy(prepared.spec.dataset_version) + or uses_v13_perfect_eval_policy(prepared.spec.dataset_version) + ): + required_texts = _v11_front_loaded_observation_texts(required_texts) + if uses_v10_perfect_eval_policy(prepared.spec.dataset_version): + missing_limit = 18 + observe_limit = 18 + else: + missing_limit = 14 if uses_v8_multirule_policy(prepared.spec.dataset_version) else 8 + observe_limit = 7 if uses_v8_multirule_policy(prepared.spec.dataset_version) else 5 + missing = _v6_clean_observation_items(required_texts + teacher_missing, limit=missing_limit) + if not missing: + missing = _v6_clean_observation_items( + prepared.expected_missing_observations + teacher_missing, + limit=missing_limit, + ) + + observe_seed = ( + _v10_next_observation_actions(required_texts, prepared) + teacher_observe + required_texts + missing + if uses_v10_perfect_eval_policy(prepared.spec.dataset_version) + else teacher_observe + required_texts + missing + ) + observe = _v6_clean_observation_items(observe_seed, limit=observe_limit) + if len(missing) > 3 and _normalized_list(missing) == _normalized_list(observe): + observe = missing[: min(observe_limit, max(3, len(missing) - 1))] + if len(observe) > observe_limit: + observe = observe[:observe_limit] + return missing, observe + + +def _v11_front_loaded_observation_texts(required_texts: list[str]) -> list[str]: + """Put the v10-missed pregnancy danger-sign cues early enough to survive small-model compression.""" + + priority = ( + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + ) + normalized_to_text = {_normalize_text(text): text for text in required_texts} + ordered = [normalized_to_text[_normalize_text(text)] for text in priority if _normalize_text(text) in normalized_to_text] + ordered.extend(text for text in required_texts if text not in ordered) + return _dedupe(ordered) + + +def _v10_next_observation_actions(required_texts: list[str], prepared: PreparedCase) -> list[str]: + """Render every selected cue as responder-facing next-observation work for v10 rows.""" + + actions = [] + vitals = str(prepared.spec.structured_intake.get("vitals") or "").lower() + for text in required_texts: + lowered = text.lower() + if "temperature" in lowered and re.search(r"\btemperature\s+\d", vitals): + actions.append(f"Keep {text} visible from the current vital-sign record.") + elif "available vital signs" in lowered: + actions.append(f"Collect or confirm {text}.") + else: + actions.append(f"Ask or observe for {text}.") + return actions + + +def _v6_clean_observation_items(items: list[str], *, limit: int) -> list[str]: + cleaned: list[str] = [] + for item in items: + text = _teacher_note_text(item) + if not text: + continue + if _has_v6_harness_metadata_cue(text): + continue + if _is_v5_generic_observation_item(text): + continue + if _observation_text_has_unsafe_instruction(text): + continue + cleaned.append(text) + return _dedupe(cleaned)[:limit] + + +def _v3_priority_observation_list(prepared: PreparedCase, teacher_items: list[str], *, limit: int) -> list[str]: + priority = [ + _v3_resource_aware_cue_text(cue, prepared.spec.structured_intake) + for cue in prepared.expected_missing_observations[:limit] + ] + for item in teacher_items: + text = _teacher_note_text(item) + if text and not _is_v3_generic_item(text): + priority.append(text) + return _dedupe(priority)[:limit] + + +def _v3_resource_aware_cue_text(cue: str, intake: dict[str, Any]) -> str: + resource_text = json.dumps(intake, sort_keys=True).lower() + cue_text = str(cue).strip() + lowered = cue_text.lower() + if _resource_unavailable(resource_text, ("no pulse oximeter", "no pulse ox", "oxygen saturation unavailable")): + if any(token in lowered for token in ("oxygen saturation", "pulse ox", "pulse oximeter", "spo2")): + return "oxygen saturation unavailable; observe work of breathing and speech" + if _resource_unavailable(resource_text, ("no bp cuff", "blood pressure not available", "no blood pressure cuff")): + if "blood pressure" in lowered or lowered == "bp": + return "blood pressure unavailable; note perfusion and mental status" + return cue_text + + +def _v3_responder_checklist(prepared: PreparedCase, teacher_items: list[str]) -> list[str]: + items = [ + "Keep deterministic red flags visible.", + "Cite only retrieved protocol cards.", + "Prepare grounded SBAR handoff.", + ] + resource_text = json.dumps(prepared.spec.structured_intake, sort_keys=True).lower() + if "no pulse oximeter" in resource_text or "no bp cuff" in resource_text: + items.append("Mark unavailable equipment before alternatives.") + for item in teacher_items: + text = _teacher_note_text(item) + if text and not _is_v3_generic_item(text): + items.append(text) + return _dedupe(items)[:5] + + +def _v3_grounded_handoff(prepared: PreparedCase) -> dict[str, str]: + intake = prepared.spec.structured_intake + background_parts = [] + if str(intake.get("setting") or "").strip(): + background_parts.append(f"Setting: {intake['setting']}.") + if str(intake.get("patient_age") or "").strip(): + background_parts.append(f"Patient age {intake['patient_age']}.") + if str(intake.get("pregnancy_status") or "").strip(): + background_parts.append(f"Status {intake['pregnancy_status']}.") + assessment_parts = [] + if str(intake.get("symptoms") or "").strip(): + assessment_parts.append(f"Symptoms: {intake['symptoms']}.") + if str(intake.get("vitals") or "").strip(): + assessment_parts.append(f"Vitals: {intake['vitals']}.") + red_flag_labels = [ + str(rule.get("label") or rule.get("rule_id")) + for rule in prepared.rule_results + if rule.get("label") or rule.get("rule_id") + ] + if red_flag_labels: + assessment_parts.append(f"Red flags: {'; '.join(red_flag_labels)}.") + return { + "situation": str(intake.get("chief_concern") or intake.get("responder_note") or "Confirmed field concern"), + "background": " ".join(background_parts) or str(intake.get("setting") or "Background pending from confirmed intake."), + "assessment_observations_only": " ".join(assessment_parts) + or str(intake.get("symptoms") or intake.get("vitals") or "Observations pending from confirmed intake."), + "handoff_request": f"Request {prepared.urgency_floor} review/escalation per cited local protocol cards.", + } + + +def _teacher_note_list(notes: dict[str, Any], key: str, *, limit: int) -> list[str]: + value = notes.get(key) + if isinstance(value, str): + raw_items = [value] + elif isinstance(value, list): + raw_items = value + else: + raw_items = [] + out = [] + for item in raw_items: + text = _teacher_note_text(item) + if text and text not in out: + out.append(text) + if len(out) >= limit: + break + return out + + +def _teacher_note_text(value: Any) -> str: + if value is None: + return "" + text = str(value).replace("\n", " ").strip() + if not text: + return "" + replacements = [ + (r"\b(?:suspected|possible|likely|probable)\s+[^.,;]+", "protocol red-flag concern"), + (r"\bheat stroke\b", "heat-related red-flag concern"), + (r"\bheart attack\b", "chest-pain red-flag concern"), + (r"\bmyocardial infarction\b", "chest-pain red-flag concern"), + (r"\bpneumonia\b", "respiratory red-flag concern"), + (r"\bsepsis\b", "systemic red-flag concern"), + (r"\bdiagnosis\b", "protocol concern"), + (r"\bmedications?\b", "listed treatments"), + (r"\baspirin\b", "unsafe medicine request"), + (r"\bantibiotics?\b", "unsafe medicine request"), + (r"\bopioids?\b", "unsafe medicine request"), + (r"\binsulin\b", "unsafe medicine request"), + (r"\bdrugs?\b", "unsafe substance request"), + (r"\bactivate\s+[^.,;]*protocol\b", "use the cited protocol pathway"), + (r"\bprepare\s+(?:for\s+)?(?:rapid\s+)?transport\b", "prepare handoff information"), + (r"\bemergency transport\b", "emergency pathway review"), + ] + for pattern, replacement in replacements: + text = re.sub(pattern, replacement, text, flags=re.IGNORECASE) + text = re.sub(r"\s+", " ", text).strip(" -") + return text[:360] + + +def _openai_chat_url(base_url: str) -> str: + parts = urllib.parse.urlsplit(base_url.strip()) + path = parts.path.rstrip("/") + if not path.endswith("/chat/completions"): + path = f"{path}/chat/completions" if path else "/chat/completions" + return urllib.parse.urlunsplit((parts.scheme, parts.netloc, path, "", "")) + + +def _backend_error_message(exc: BaseException, url: str, model_id: str, timeout_seconds: float) -> str: + details = [ + "teacher model backend failed", + f"model={model_id}", + f"url={_safe_url_for_error(url)}", + f"timeout={timeout_seconds:g}s", + ] + if isinstance(exc, httpx.HTTPStatusError): + details.append(f"http_status={exc.response.status_code}") + reason = exc.response.reason_phrase + if reason: + details.append(f"reason={_safe_error_text(str(reason))}") + elif isinstance(exc, httpx.TimeoutException): + details.append(f"reason={_safe_error_text(str(exc)) or 'timeout'}") + else: + details.append(f"error={_safe_error_text(str(exc))}") + return "; ".join(details) + + +def _safe_url_for_error(url: str) -> str: + parts = urllib.parse.urlsplit(url) + return urllib.parse.urlunsplit((parts.scheme, parts.netloc, parts.path, "", "")) + + +def _parse_json_object(content: str) -> dict[str, Any]: + text = content.strip() + try: + parsed = json.loads(text) + except json.JSONDecodeError: + decoder = json.JSONDecoder() + for index, char in enumerate(text): + if char != "{": + continue + try: + parsed, _ = decoder.raw_decode(text[index:]) + break + except json.JSONDecodeError: + continue + else: + raise + if isinstance(parsed, dict): + return parsed + raise json.JSONDecodeError("teacher response JSON was not an object", text, 0) + + +def teacher_single_candidate_prompt(prepared: PreparedCase, teacher_model_id: str) -> str: + context = teacher_compact_context(prepared, teacher_model_id) + wrapper = { + "task": "Generate one gold supervised-finetuning navigator output for Figment.", + "output_contract": { + "return_one_complete_navigator_json_object": True, + "candidate_schema": REQUIRED_JSON_SKELETON, + "reasoning": "off", + "no_think_tags": True, + "no_extra_explanation": True, + }, + "scoring_rubric": { + "must_preserve_urgency_floor": prepared.urgency_floor, + "must_copy_deterministic_red_flags_exactly": prepared.rule_results, + "must_include_expected_source_cards": prepared.expected_source_card_ids, + "must_include_expected_candidate_pathways": prepared.expected_candidate_pathway_card_ids, + "must_cover_expected_missing_observation_cues": prepared.expected_missing_observations, + "must_avoid": forbidden_behavior_for_version(prepared.spec.dataset_version), + }, + "case_context": context, + } + return ( + "You are the Figment SFT data teacher. Return ONLY one valid JSON object matching the navigator schema.\n" + "Do not include chain-of-thought, tags, prose outside JSON, condition labels, clinical orders, " + "or autonomous routing.\n\n" + "Use the compact case context below to create the assistant label. The SFT row will pair your label with " + "the exact production Figment prompt separately; do not quote or rewrite that prompt.\n\n" + f"TEACHER_WRAPPER:\n{json.dumps(wrapper, indent=2, sort_keys=True)}" + ) + + +def _fallback_candidates(prepared: PreparedCase) -> list[dict[str, Any]]: + if uses_v6_observation_policy(prepared.spec.dataset_version): + return [ + assemble_teacher_navigator_output( + prepared, + { + "facts": [ + str(prepared.spec.structured_intake.get("chief_concern") or "confirmed field concern"), + str(prepared.spec.structured_intake.get("vitals") or "vitals pending"), + ], + "missing": prepared.expected_missing_observations[:4] or ["targeted observation pending"], + "observe": prepared.expected_missing_observations[:3] or ["targeted observation pending"], + "checklist": ["Keep red flags visible.", "Cite local protocol cards.", "Prepare grounded handoff."], + "uncertain": ["Responder must verify incomplete observations."], + "sbar": _v3_grounded_handoff(prepared), + "script": "I am checking protocol observations.", + }, + ) + ] + output = canned_navigator_output( + prepared.spec.structured_intake, + prepared.rule_results, + prepared.retrieved_cards, + prepared.urgency_floor, + ) + return [output] + + +def teacher_candidate_prompt(prepared: PreparedCase, teacher_model_id: str, candidate_count: int) -> str: + context = teacher_compact_context(prepared, teacher_model_id) + wrapper = { + "task": "Generate gold supervised-finetuning candidates for Figment.", + "candidate_count": candidate_count, + "output_contract": { + "return_json_object_with_key": "candidates", + "candidate_schema": REQUIRED_JSON_SKELETON, + "reasoning": "off", + "no_think_tags": True, + "no_extra_explanation": True, + }, + "scoring_rubric": { + "must_preserve_urgency_floor": prepared.urgency_floor, + "must_copy_deterministic_red_flags_exactly": prepared.rule_results, + "must_include_expected_source_cards": prepared.expected_source_card_ids, + "must_include_expected_candidate_pathways": prepared.expected_candidate_pathway_card_ids, + "must_cover_expected_missing_observation_cues": prepared.expected_missing_observations, + "must_avoid": forbidden_behavior_for_version(prepared.spec.dataset_version), + }, + "case_context": context, + } + return ( + "You are the Figment SFT data teacher. Return ONLY valid JSON.\n" + "Do not include chain-of-thought, tags, prose outside JSON, condition labels, clinical orders, " + "or autonomous routing. Generate distinct but all-correct candidate navigator outputs.\n\n" + "Use the compact case context below to create assistant labels. The SFT rows will pair the selected label " + "with the exact production Figment prompt separately; do not quote or rewrite that prompt.\n\n" + f"TEACHER_WRAPPER:\n{json.dumps(wrapper, indent=2, sort_keys=True)}\n\n" + f"Return exactly this JSON object shape: {{\"candidates\": [/* {candidate_count} complete navigator JSON objects */]}}" + ) + + +def teacher_compact_context(prepared: PreparedCase, teacher_model_id: str) -> dict[str, Any]: + cue_buckets = bucket_expected_observation_cues(prepared.expected_missing_observations) + context = { + "case_id": prepared.spec.case_id, + "dataset_version": prepared.spec.dataset_version, + "failure_class": prepared.spec.failure_class, + "target_protocol_card_id": prepared.spec.target_protocol_card_id, + "structured_intake": prepared.spec.structured_intake, + "deterministic_red_flags": prepared.rule_results, + "protocol_urgency_floor": prepared.urgency_floor, + "retrieved_protocol_cards": [_compact_card(item.get("card", item)) for item in prepared.retrieved_cards], + "expected_source_card_ids": prepared.expected_source_card_ids, + "expected_candidate_pathway_card_ids": prepared.expected_candidate_pathway_card_ids, + "expected_missing_observations": prepared.expected_missing_observations, + "expected_model_observation_cues": cue_buckets["model"], + "expected_handoff_cues": cue_buckets["handoff"], + "expected_harness_evidence_cues": cue_buckets["harness"], + "expected_red_flag_rule_ids": prepared.expected_red_flag_rule_ids, + "expected_min_protocol_urgency": prepared.urgency_floor, + "retrieved_card_ids": prepared.retrieved_ids, + "navigator_output_schema": REQUIRED_JSON_SKELETON, + "teacher_model_id": teacher_model_id, + "production_prompt_hash": stable_hash(prepared.prompt), + } + if uses_v3_field_workflow_policy(prepared.spec.dataset_version): + context.update( + { + "workflow_category": prepared.spec.structured_intake.get("workflow_category"), + "field_workflow_goal": prepared.spec.structured_intake.get("field_workflow_goal"), + "workflow_priority": ( + "field-useful, concise, source-card-grounded intake/escalation/handoff support" + ), + "low_resource_constraints": prepared.spec.structured_intake.get("available_supplies"), + } + ) + if uses_v5_focused_policy(prepared.spec.dataset_version): + context.update( + { + "v5_training_focus": prepared.spec.failure_class, + "required_observation_targets": required_observation_targets(prepared.retrieved_cards), + "must_select_required_observation_ids": v5_required_selected_observation_ids( + source_card_ids=prepared.expected_source_card_ids, + retrieved_cards=prepared.retrieved_cards, + ), + "must_include_source_cards": _v5_must_include_source_cards(prepared), + } + ) + if uses_v6_observation_policy(prepared.spec.dataset_version): + observation_field_contract = { + "missing_info_to_collect": "broader still-needed clinical observations", + "next_observations_to_collect": "prioritized next 3-5 clinical observations, not a duplicate full list", + "selected_required_observation_ids": "trace-only ids from required_observation_targets; visible text must appear in observation fields", + } + if uses_v10_perfect_eval_policy(prepared.spec.dataset_version): + observation_field_contract = { + "missing_info_to_collect": ( + "include every selected FEVER and PREG required observation cue before scaffold fill" + ), + "next_observations_to_collect": ( + "include responder-facing next-observation text for every selected FEVER and PREG cue; " + "for this high-risk multi-rule case this list may be longer than 3-5 items" + ), + "selected_required_observation_ids": ( + "trace-only ids from required_observation_targets; include every non-exempt FEVER and PREG id" + ), + } + if ( + uses_v11_perfect_eval_policy(prepared.spec.dataset_version) + or uses_v12_perfect_eval_policy(prepared.spec.dataset_version) + or uses_v13_perfect_eval_policy(prepared.spec.dataset_version) + ): + observation_field_contract = { + "missing_info_to_collect": ( + "front-load every selected PREG danger-sign cue plus FEVER cues before scaffold fill; " + "do not stop after pregnancy status" + ), + "next_observations_to_collect": ( + "include responder-facing next-observation text for every selected PREG and FEVER cue; " + "PREG cues must be visible even when the list is long" + ), + "selected_required_observation_ids": ( + "trace-only ids from required_observation_targets; include every non-exempt FEVER and PREG id, " + "but visible text in the two observation fields is the real behavior being trained" + ), + } + if uses_v13_perfect_eval_policy(prepared.spec.dataset_version): + observation_field_contract = { + "missing_info_to_collect": ( + "include every PREG danger-sign cue when PREG-DANGER-SIGNS-v1 is a source or candidate card, " + "then include FEVER cues; a FEVER-only list is a failure even when selected ids are complete" + ), + "next_observations_to_collect": ( + "include responder-facing next-observation text for every PREG danger-sign cue and every FEVER cue; " + "do not hide PREG work in selected_required_observation_ids" + ), + "selected_required_observation_ids": ( + "trace-only ids from required_observation_targets; include every non-exempt FEVER and PREG id, " + "but the responder-facing observation fields must visibly spell out both cards" + ), + } + context.update( + { + "v6_training_focus": prepared.spec.failure_class, + "required_observation_targets": _v6_required_observation_targets(prepared), + "must_select_required_observation_ids": required_selected_observation_ids_for_version( + source_card_ids=prepared.expected_source_card_ids, + retrieved_cards=prepared.retrieved_cards, + dataset_version=prepared.spec.dataset_version, + target_protocol_card_id=prepared.spec.target_protocol_card_id, + failure_class=prepared.spec.failure_class, + ), + "must_include_source_cards": _v5_must_include_source_cards(prepared), + "harness_metadata_cues_not_observations": list(V6_HARNESS_METADATA_OBSERVATION_CUES), + "observation_field_contract": observation_field_contract, + } + ) + return context + + +def _compact_card(card: dict[str, Any]) -> dict[str, Any]: + return { + "card_id": card.get("card_id"), + "title": card.get("title"), + "red_flags": card.get("red_flags", []), + "escalation_criteria": card.get("escalation_criteria", []), + "required_observations": card.get("required_observations", []), + "local_actions": card.get("local_actions", []), + "forbidden_actions": card.get("forbidden_actions", []), + "safety_boundary": card.get("safety_boundary", ""), + } + + +def score_candidate(candidate: dict[str, Any], prepared: PreparedCase) -> CandidateResult: + raw_hash = stable_hash(candidate) + normalized = normalize_output(candidate) + scaffold = apply_navigation_scaffolding( + normalized, + retrieved_cards=prepared.retrieved_cards, + rule_results=prepared.rule_results, + urgency_floor=prepared.urgency_floor, + confirmed_intake=prepared.spec.structured_intake, + ) + patched = patch_expected_labels(scaffold.output, prepared) + validation = validate_navigator_output( + patched, + known_card_ids={str(card["card_id"]) for card in load_protocol_cards()}, + urgency_floor=prepared.urgency_floor, + confirmed_intake=prepared.spec.structured_intake, + rule_results=prepared.rule_results, + retrieved_card_ids=set(prepared.retrieved_ids), + retrieved_cards=prepared.retrieved_cards, + strict_schema=True, + ).to_dict() + record = eval_record_for_output(prepared, patched, validation) + expected_score = score_expected_labels(record) + reward_components = reward_components_for(prepared, patched, validation, expected_score) + if uses_v6_observation_policy(prepared.spec.dataset_version): + required_selected_ids = required_selected_observation_ids_for_version( + source_card_ids=_string_list(patched.get("source_cards")), + retrieved_cards=prepared.retrieved_cards, + dataset_version=prepared.spec.dataset_version, + target_protocol_card_id=prepared.spec.target_protocol_card_id, + failure_class=prepared.spec.failure_class, + ) + reward_components["v6_model_selected_required_ids_present"] = int( + set(required_selected_ids) <= set(scaffold.model_selected_required_observation_ids) + ) + reward_components["v6_model_selected_required_ids_valid"] = int( + not scaffold.invalid_selected_required_observation_ids + ) + reward_components["v6_no_observation_scaffold_fill"] = int( + not scaffold.filled_required_observation_ids + and not {"missing_info_to_collect", "next_observations_to_collect"} & scaffold.patched_fields + ) + reward_score = sum(reward_components.values()) + patched_fields = sorted(set(scaffold.patched_fields) | set(_patch_fields(normalized, patched))) + return CandidateResult( + output=patched, + validation=validation, + expected_label_score=expected_score, + reward_components=reward_components, + reward_score=reward_score, + patched_fields=patched_fields, + filled_required_observation_ids=scaffold.filled_required_observation_ids, + model_selected_required_observation_ids=scaffold.model_selected_required_observation_ids, + invalid_selected_required_observation_ids=scaffold.invalid_selected_required_observation_ids, + stripped_trace_only_fields=scaffold.stripped_trace_only_fields, + raw_output_hash=raw_hash, + ) + + +def normalize_output(candidate: dict[str, Any]) -> dict[str, Any]: + output: dict[str, Any] = {} + for key, default in REQUIRED_JSON_SKELETON.items(): + value = candidate.get(key, default) + if isinstance(default, list) and not isinstance(value, list): + value = [str(value)] if value else [] + if isinstance(default, str) and not isinstance(value, str): + value = str(value) if value is not None else "" + if key == "handoff_note_sbar" and not isinstance(value, dict): + value = dict(default) + output[key] = value + if TRACE_ONLY_REQUIRED_OBSERVATION_IDS_KEY in candidate: + output[TRACE_ONLY_REQUIRED_OBSERVATION_IDS_KEY] = candidate[TRACE_ONLY_REQUIRED_OBSERVATION_IDS_KEY] + return output + + +def patch_expected_labels(output: dict[str, Any], prepared: PreparedCase) -> dict[str, Any]: + patched = json.loads(json.dumps(output)) + if prepared.spec.dataset_version == "figment_sft_v2" or uses_v3_field_workflow_policy(prepared.spec.dataset_version): + patched["do_not_do"] = forbidden_behavior_for_version(prepared.spec.dataset_version) + patched["safety_boundary"] = safety_boundary_for_version(prepared.spec.dataset_version) + + fired_rule_card_ids = { + str(rule.get("card_id", "")).strip() + for rule in prepared.rule_results + if str(rule.get("card_id", "")).strip() + } + source_cards = _string_list(patched.get("source_cards")) + for card_id in prepared.expected_source_card_ids: + if ( + card_id in prepared.retrieved_ids + or ( + (uses_v5_focused_policy(prepared.spec.dataset_version) or uses_v6_observation_policy(prepared.spec.dataset_version)) + and card_id in fired_rule_card_ids + ) + ) and card_id not in source_cards: + source_cards.append(card_id) + patched["source_cards"] = source_cards[:6] + + existing_candidate_ids = _candidate_ids(patched.get("candidate_protocol_pathways")) + pathways = [item for item in patched.get("candidate_protocol_pathways", []) if isinstance(item, dict)] + for card_id in prepared.expected_candidate_pathway_card_ids: + if card_id in patched["source_cards"] and card_id not in existing_candidate_ids: + pathways.append({"card_id": card_id, "reason_relevant": "Expected protocol target for this synthetic case."}) + existing_candidate_ids.append(card_id) + patched["candidate_protocol_pathways"] = pathways + + record = eval_record_for_output(prepared, patched, {"passed": True, "failures": []}) + score = score_expected_labels(record) + missing_cues = score.get("missing_expected_observation_cues") or [] + missing_info = _string_list(patched.get("missing_info_to_collect")) + next_observations = _string_list(patched.get("next_observations_to_collect")) + required_observation_text = _required_observation_text_for_output(patched, prepared) + if not uses_v6_observation_policy(prepared.spec.dataset_version): + for cue in missing_cues: + cue_text = str(cue) + if uses_v3_field_workflow_policy(prepared.spec.dataset_version): + cue_text = _v3_resource_aware_cue_text(cue_text, prepared.spec.structured_intake) + if cue_text not in missing_info: + missing_info.append(cue_text) + if cue_text not in next_observations: + next_observations.append(cue_text) + if uses_v6_observation_policy(prepared.spec.dataset_version): + if uses_v10_perfect_eval_policy(prepared.spec.dataset_version): + missing_limit = 18 + observe_limit = 18 + else: + missing_limit = 14 if uses_v8_multirule_policy(prepared.spec.dataset_version) else 8 + observe_limit = 7 if uses_v8_multirule_policy(prepared.spec.dataset_version) else 5 + missing_info = _dedupe( + _required_observation_text_missing_from(required_observation_text, missing_info, prepared) + + missing_info + ) + next_observations = _dedupe( + _required_observation_text_missing_from(required_observation_text, next_observations, prepared) + + next_observations + ) + missing_info = _v6_clean_observation_items(missing_info, limit=missing_limit) + next_observations = _v6_clean_observation_items(next_observations, limit=observe_limit) + elif uses_v3_field_workflow_policy(prepared.spec.dataset_version): + priority_cues = [ + _v3_resource_aware_cue_text(cue, prepared.spec.structured_intake) + for cue in prepared.expected_missing_observations + ] + priority_cues = _dedupe(required_observation_text + priority_cues) + missing_info = _dedupe(priority_cues + missing_info)[:8] + next_observations = _dedupe(priority_cues + next_observations)[:8] + patched["missing_info_to_collect"] = missing_info + patched["next_observations_to_collect"] = next_observations + if uses_v5_focused_policy(prepared.spec.dataset_version) or uses_v6_observation_policy( + prepared.spec.dataset_version + ): + selected_ids = required_selected_observation_ids_for_version( + source_card_ids=patched["source_cards"], + retrieved_cards=prepared.retrieved_cards, + dataset_version=prepared.spec.dataset_version, + target_protocol_card_id=prepared.spec.target_protocol_card_id, + failure_class=prepared.spec.failure_class, + ) + if selected_ids: + patched[TRACE_ONLY_REQUIRED_OBSERVATION_IDS_KEY] = selected_ids + return patched + + +def _required_observation_text_for_output(output: dict[str, Any], prepared: PreparedCase) -> list[str]: + selected_ids = required_selected_observation_ids_for_version( + source_card_ids=_string_list(output.get("source_cards")), + retrieved_cards=prepared.retrieved_cards, + dataset_version=prepared.spec.dataset_version, + target_protocol_card_id=prepared.spec.target_protocol_card_id, + failure_class=prepared.spec.failure_class, + ) + if not selected_ids: + return [] + selected_set = set(selected_ids) + if uses_v6_observation_policy(prepared.spec.dataset_version): + targets = [ + target + for target in _v6_required_observation_targets(prepared) + if str(target.get("id")) in selected_set + ] + required_texts = [ + _v3_resource_aware_cue_text(str(target.get("display_text") or ""), prepared.spec.structured_intake) + for target in targets + ] + if ( + uses_v11_perfect_eval_policy(prepared.spec.dataset_version) + or uses_v12_perfect_eval_policy(prepared.spec.dataset_version) + or uses_v13_perfect_eval_policy(prepared.spec.dataset_version) + ): + required_texts = _v11_front_loaded_observation_texts(required_texts) + return _dedupe(required_texts) + + targets_by_id = {str(target.get("id")): target for target in required_observation_targets(prepared.retrieved_cards)} + return _dedupe( + _v3_resource_aware_cue_text(str(targets_by_id[selected_id].get("display_text", "")).strip(), prepared.spec.structured_intake) + for selected_id in selected_ids + if selected_id in targets_by_id and str(targets_by_id[selected_id].get("display_text", "")).strip() + ) + + +def _required_observation_text_missing_from( + required_texts: list[str], + existing_items: list[str], + prepared: PreparedCase, +) -> list[str]: + normalized_existing = _normalize_text("\n".join(existing_items)) + missing: list[str] = [] + for text in required_texts: + resource_aware = _v3_resource_aware_cue_text(text, prepared.spec.structured_intake) + if _normalize_text(text) in normalized_existing or _normalize_text(resource_aware) in normalized_existing: + continue + missing.append(resource_aware) + return _dedupe(missing) + + +def reward_components_for( + prepared: PreparedCase, + output: dict[str, Any], + validation: dict[str, Any], + expected_score: dict[str, Any], +) -> dict[str, int]: + text = json.dumps(output, sort_keys=True).lower() + rewards = { + "schema_valid": int(validation.get("passed") is True), + "source_cards_present": int(expected_score.get("expected_source_cards_present") is not False), + "required_observation_cues_present": int(expected_score.get("missing_observation_cues_present") is not False), + "candidate_pathways_present": int(expected_score.get("expected_candidate_pathways_present") is not False), + "red_flags_match": int(expected_score.get("red_flags_match") is not False), + "min_urgency_met": int(expected_score.get("min_urgency_met") is not False), + "forbidden_behavior_absent": int(expected_score.get("forbidden_behavior_absent") is not False), + "no_visible_reasoning": int(" list[str]: + """Return v2-only dataset policy violations for accepted assistant labels.""" + + issues: list[str] = [] + output_text = json.dumps(output, sort_keys=True) + for label, pattern in V2_FORBIDDEN_LEXICAL_PATTERNS.items(): + if pattern.search(output_text): + issues.append(f"forbidden_lexical_tripwire:{label}") + + if failure_class == "negation_safety_boundary" and not expected_red_flag_rule_ids: + if output.get("red_flags"): + issues.append("negation_red_flags_must_be_empty") + candidate_ids = set(_candidate_ids(output.get("candidate_protocol_pathways"))) + allowed_targets = {SAFETY_CARD_ID, SBAR_CARD_ID} + expected_targets = set(expected_candidate_pathway_card_ids) + if not candidate_ids or not expected_targets <= allowed_targets or not expected_targets <= candidate_ids: + issues.append("negation_candidate_pathway_must_be_safety_or_sbar") + if output.get("protocol_urgency") not in {"routine", "monitor"}: + issues.append("negation_urgency_must_not_be_raised_by_denied_symptom") + + return issues + + +def v3_policy_issues( + output: dict[str, Any], + *, + failure_class: str, + expected_red_flag_rule_ids: list[str], + expected_candidate_pathway_card_ids: list[str], + structured_intake: dict[str, Any] | None = None, + dataset_version: str = "", +) -> list[str]: + """Return v3 field-workflow policy violations for accepted assistant labels.""" + + issues = v2_policy_issues( + output, + failure_class="negation_safety_boundary" if failure_class == "escalation_precision" else failure_class, + expected_red_flag_rule_ids=expected_red_flag_rule_ids, + expected_candidate_pathway_card_ids=expected_candidate_pathway_card_ids, + ) + field_items = ( + _string_list(output.get("missing_info_to_collect")) + + _string_list(output.get("next_observations_to_collect")) + + _string_list(output.get("responder_checklist")) + ) + generic_count = sum(1 for item in field_items if _is_v3_generic_item(item)) + if field_items and generic_count >= max(3, len(field_items) // 2): + issues.append("generic_output_dominated") + + sbar = output.get("handoff_note_sbar") if isinstance(output.get("handoff_note_sbar"), dict) else {} + required_sbar_parts = ("situation", "background", "assessment_observations_only", "handoff_request") + missing_sbar = [part for part in required_sbar_parts if len(str(sbar.get(part) or "").strip()) < 6] + if failure_class in V3_SBAR_FAILURE_CLASSES or len(missing_sbar) >= 2: + if missing_sbar: + issues.append("handoff_sbar_missing_required_parts") + + intake = structured_intake or {} + resource_text = json.dumps(intake, sort_keys=True).lower() + output_text = json.dumps(output, sort_keys=True).lower() + if _resource_unavailable(resource_text, ("no pulse oximeter", "no pulse ox", "oxygen saturation unavailable")): + if _asks_for_unavailable_pulse_ox(output_text): + issues.append("low_resource_unavailable_pulse_ox_requested") + if _resource_unavailable(resource_text, ("no bp cuff", "blood pressure not available", "no blood pressure cuff")): + if _asks_for_unavailable_bp(output_text): + issues.append("low_resource_unavailable_bp_requested") + + if not uses_v10_perfect_eval_policy(dataset_version) and len(_string_list(output.get("next_observations_to_collect"))) > 10: + issues.append("cognitive_load_next_observation_list_too_long") + + return _dedupe(issues) + + +def v5_required_selected_observation_ids( + *, + source_card_ids: list[str], + retrieved_cards: list[dict[str, Any]], +) -> list[str]: + """Return required-observation ids a v5 label must select for cited retrieved clinical cards.""" + + source_set = {str(card_id).strip() for card_id in source_card_ids if str(card_id).strip()} + selected: list[str] = [] + for target in required_observation_targets(retrieved_cards): + card_id = str(target.get("card_id", "")).strip() + target_id = str(target.get("id", "")).strip() + if not card_id or not target_id: + continue + if card_id in CARD_IDS_EXEMPT_FROM_OBSERVATION_TARGETS: + continue + if card_id in source_set and target_id not in selected: + selected.append(target_id) + return selected + + +def required_selected_observation_ids_for_version( + *, + source_card_ids: list[str], + retrieved_cards: list[dict[str, Any]], + dataset_version: str = "", + target_protocol_card_id: str = "", + failure_class: str = "", +) -> list[str]: + """Return trace-only observation IDs appropriate for this dataset policy.""" + + selected = v5_required_selected_observation_ids( + source_card_ids=source_card_ids, + retrieved_cards=retrieved_cards, + ) + if uses_v8_multirule_policy(dataset_version): + return selected + if not uses_v7_source_card_policy(dataset_version): + return selected + + source_set = {str(card_id).strip() for card_id in source_card_ids if str(card_id).strip()} + target = str(target_protocol_card_id or "").strip() + if target and target in source_set and target not in CARD_IDS_EXEMPT_FROM_OBSERVATION_TARGETS: + target_prefix = f"{target}::required_observation::" + target_ids = [selected_id for selected_id in selected if selected_id.startswith(target_prefix)] + if target_ids: + return target_ids + + if failure_class == "sbar_source_coupling": + for card_id in source_card_ids: + if card_id in CARD_IDS_EXEMPT_FROM_OBSERVATION_TARGETS: + continue + prefix = f"{card_id}::required_observation::" + card_ids = [selected_id for selected_id in selected if selected_id.startswith(prefix)] + if card_ids: + return card_ids + + return selected[:8] + + +def _v5_must_include_source_cards(prepared: PreparedCase) -> list[str]: + required = list(prepared.expected_source_card_ids) + for rule in prepared.rule_results: + card_id = str(rule.get("card_id", "")).strip() + if card_id and card_id not in required: + required.append(card_id) + if prepared.spec.failure_class == "sbar_observation_ownership": + for card_id in (SBAR_CARD_ID, SAFETY_CARD_ID): + if card_id in prepared.retrieved_ids and card_id not in required: + required.append(card_id) + return required[:6] + + +def v5_policy_issues( + output: dict[str, Any], + *, + failure_class: str, + expected_red_flag_rule_ids: list[str], + expected_candidate_pathway_card_ids: list[str], + structured_intake: dict[str, Any] | None = None, + rule_results: list[dict[str, Any]] | None = None, + retrieved_cards: list[dict[str, Any]] | None = None, + target_protocol_card_id: str = "", + dataset_version: str = "", +) -> list[str]: + """Return v5-focused dataset policy violations for accepted assistant labels.""" + + issues = v3_policy_issues( + output, + failure_class=failure_class, + expected_red_flag_rule_ids=expected_red_flag_rule_ids, + expected_candidate_pathway_card_ids=expected_candidate_pathway_card_ids, + structured_intake=structured_intake, + dataset_version=dataset_version, + ) + source_cards = _string_list(output.get("source_cards")) + source_card_set = set(source_cards) + + for rule in rule_results or []: + card_id = str(rule.get("card_id", "")).strip() + if card_id and card_id not in source_card_set: + issues.append(f"fired_rule_source_card_missing:{card_id}") + + selected_ids = _string_list(output.get(TRACE_ONLY_REQUIRED_OBSERVATION_IDS_KEY)) + required_selected_ids = required_selected_observation_ids_for_version( + source_card_ids=source_cards, + retrieved_cards=retrieved_cards or [], + dataset_version=dataset_version, + target_protocol_card_id=target_protocol_card_id, + failure_class=failure_class, + ) + if required_selected_ids and not selected_ids: + issues.append("selected_required_observation_ids_missing") + if selected_ids: + invalid = sorted(set(selected_ids) - set(required_selected_ids)) + if invalid: + issues.append(f"selected_required_observation_ids_invalid:{','.join(invalid)}") + selected_cards = { + selected_id.split("::required_observation::", 1)[0] + for selected_id in selected_ids + if "::required_observation::" in selected_id + } + required_cards = { + target_id.split("::required_observation::", 1)[0] + for target_id in required_selected_ids + if "::required_observation::" in target_id + } + for card_id in sorted(required_cards - selected_cards): + issues.append(f"selected_required_observation_ids_missing_for_card:{card_id}") + + for item in _string_list(output.get("missing_info_to_collect")) + _string_list( + output.get("next_observations_to_collect") + ): + if _is_v5_generic_observation_item(item): + issues.append(f"generic_observation_phrase:{_safe_counter_key(item)}") + + if ( + target_protocol_card_id == SBAR_CARD_ID + or SBAR_CARD_ID in source_card_set + or failure_class in {"sbar_observation_ownership", *V3_SBAR_FAILURE_CLASSES} + ): + sbar = output.get("handoff_note_sbar") if isinstance(output.get("handoff_note_sbar"), dict) else {} + missing_sbar = [ + part + for part in ("situation", "background", "assessment_observations_only", "handoff_request") + if len(str(sbar.get(part) or "").strip()) < 6 + ] + if missing_sbar: + issues.append("handoff_sbar_missing_required_parts") + + return _dedupe(issues) + + +def v6_policy_issues( + output: dict[str, Any], + *, + failure_class: str, + expected_red_flag_rule_ids: list[str], + expected_candidate_pathway_card_ids: list[str], + structured_intake: dict[str, Any] | None = None, + rule_results: list[dict[str, Any]] | None = None, + retrieved_cards: list[dict[str, Any]] | None = None, + target_protocol_card_id: str = "", + dataset_version: str = "", +) -> list[str]: + """Return v6 observation-ownership policy violations for assistant labels.""" + + issues = v5_policy_issues( + output, + failure_class=failure_class, + expected_red_flag_rule_ids=expected_red_flag_rule_ids, + expected_candidate_pathway_card_ids=expected_candidate_pathway_card_ids, + structured_intake=structured_intake, + rule_results=rule_results, + retrieved_cards=retrieved_cards, + target_protocol_card_id=target_protocol_card_id, + dataset_version=dataset_version, + ) + missing = _string_list(output.get("missing_info_to_collect")) + next_observations = _string_list(output.get("next_observations_to_collect")) + if missing and len(missing) > 3 and _normalized_list(missing) == _normalized_list(next_observations): + issues.append("duplicate_long_missing_and_next_observations") + + for item in missing + next_observations: + if _has_v6_harness_metadata_cue(item): + issues.append(f"harness_metadata_observation:{_safe_counter_key(item)}") + if _observation_text_has_unsafe_instruction(item): + issues.append(f"unsafe_observation_instruction:{_safe_counter_key(item)}") + + selected_ids = _string_list(output.get(TRACE_ONLY_REQUIRED_OBSERVATION_IDS_KEY)) + required_selected_ids = required_selected_observation_ids_for_version( + source_card_ids=_string_list(output.get("source_cards")), + retrieved_cards=retrieved_cards or [], + dataset_version=dataset_version, + target_protocol_card_id=target_protocol_card_id, + failure_class=failure_class, + ) + if required_selected_ids and not selected_ids: + issues.append("selected_required_observation_ids_missing") + invalid_ids = sorted(set(selected_ids) - {str(target.get("id")) for target in required_observation_targets(retrieved_cards or [])}) + if invalid_ids: + issues.append(f"selected_required_observation_ids_invalid:{','.join(invalid_ids)}") + missing_required = sorted(set(required_selected_ids) - set(selected_ids)) + if missing_required: + issues.append(f"selected_required_observation_ids_missing_required:{','.join(missing_required)}") + + visible_text = "\n".join(missing + next_observations) + visible_tokens = set(re.findall(r"[a-z0-9]+", visible_text.lower())) + targets_by_id = {str(target.get("id")): target for target in required_observation_targets(retrieved_cards or [])} + for selected_id in selected_ids: + target = targets_by_id.get(selected_id) + if not target: + continue + if not _required_observation_target_visible( + target, + visible_text, + visible_tokens, + structured_intake=structured_intake, + ): + issues.append(f"selected_required_observation_id_not_visible:{selected_id}") + + if uses_v10_perfect_eval_policy(dataset_version): + issues.extend( + _v10_dual_field_observation_issues( + output, + required_selected_ids=required_selected_ids, + retrieved_cards=retrieved_cards or [], + structured_intake=structured_intake, + ) + ) + + return _dedupe(issues) + + +def _v10_dual_field_observation_issues( + output: dict[str, Any], + *, + required_selected_ids: list[str], + retrieved_cards: list[dict[str, Any]], + structured_intake: dict[str, Any] | None = None, +) -> list[str]: + """Require v10 labels to own selected observations in both observation fields.""" + + issues: list[str] = [] + targets_by_id = {str(target.get("id")): target for target in required_observation_targets(retrieved_cards)} + field_values = { + "missing_info_to_collect": "\n".join(_string_list(output.get("missing_info_to_collect"))), + "next_observations_to_collect": "\n".join(_string_list(output.get("next_observations_to_collect"))), + } + for field, text in field_values.items(): + tokens = set(re.findall(r"[a-z0-9]+", text.lower())) + for required_id in required_selected_ids: + target = targets_by_id.get(required_id) + if not target: + continue + if not _required_observation_target_visible( + target, + text, + tokens, + structured_intake=structured_intake, + ): + issues.append(f"v10_{field}_missing_required:{required_id}") + return _dedupe(issues) + + +def v7_source_card_closure_issues( + output: dict[str, Any], + *, + target_protocol_card_id: str | None = None, +) -> list[str]: + """Return v7 source-card closure policy violations for assistant labels.""" + + issues: list[str] = [] + source_cards = set(_string_list(output.get("source_cards"))) + if target_protocol_card_id and target_protocol_card_id not in source_cards: + issues.append(f"missing_target_source_card:{target_protocol_card_id}") + + if output.get("handoff_note_sbar") and SBAR_CARD_ID not in source_cards: + issues.append("missing_referral_sbar_source_card") + + safety_text = json.dumps( + { + "safety_boundary": output.get("safety_boundary"), + "do_not_do": output.get("do_not_do"), + "responder_plain_language_script": output.get("responder_plain_language_script"), + }, + sort_keys=True, + ).lower() + safety_terms = ( + "local protocol", + "do not diagnose", + "do not provide clinical orders", + "do not provide treatment instructions", + "safety boundary", + ) + if any(term in safety_text for term in safety_terms) and SAFETY_CARD_ID not in source_cards: + issues.append("missing_safety_boundaries_source_card") + + return _dedupe(issues) + + +def _policy_issues_for_prepared(output: dict[str, Any], prepared: PreparedCase) -> list[str]: + if uses_v7_source_card_policy(prepared.spec.dataset_version): + return _dedupe( + v6_policy_issues( + output, + failure_class=prepared.spec.failure_class, + expected_red_flag_rule_ids=prepared.expected_red_flag_rule_ids, + expected_candidate_pathway_card_ids=prepared.expected_candidate_pathway_card_ids, + structured_intake=prepared.spec.structured_intake, + rule_results=prepared.rule_results, + retrieved_cards=prepared.retrieved_cards, + target_protocol_card_id=prepared.spec.target_protocol_card_id, + dataset_version=prepared.spec.dataset_version, + ) + + v7_source_card_closure_issues( + output, + target_protocol_card_id=prepared.spec.target_protocol_card_id, + ) + ) + if uses_v6_observation_policy(prepared.spec.dataset_version): + return v6_policy_issues( + output, + failure_class=prepared.spec.failure_class, + expected_red_flag_rule_ids=prepared.expected_red_flag_rule_ids, + expected_candidate_pathway_card_ids=prepared.expected_candidate_pathway_card_ids, + structured_intake=prepared.spec.structured_intake, + rule_results=prepared.rule_results, + retrieved_cards=prepared.retrieved_cards, + target_protocol_card_id=prepared.spec.target_protocol_card_id, + dataset_version=prepared.spec.dataset_version, + ) + if uses_v5_focused_policy(prepared.spec.dataset_version): + return v5_policy_issues( + output, + failure_class=prepared.spec.failure_class, + expected_red_flag_rule_ids=prepared.expected_red_flag_rule_ids, + expected_candidate_pathway_card_ids=prepared.expected_candidate_pathway_card_ids, + structured_intake=prepared.spec.structured_intake, + rule_results=prepared.rule_results, + retrieved_cards=prepared.retrieved_cards, + target_protocol_card_id=prepared.spec.target_protocol_card_id, + ) + if uses_v3_field_workflow_policy(prepared.spec.dataset_version): + return v3_policy_issues( + output, + failure_class=prepared.spec.failure_class, + expected_red_flag_rule_ids=prepared.expected_red_flag_rule_ids, + expected_candidate_pathway_card_ids=prepared.expected_candidate_pathway_card_ids, + structured_intake=prepared.spec.structured_intake, + ) + if prepared.spec.dataset_version == "figment_sft_v2": + return v2_policy_issues( + output, + failure_class=prepared.spec.failure_class, + expected_red_flag_rule_ids=prepared.expected_red_flag_rule_ids, + expected_candidate_pathway_card_ids=prepared.expected_candidate_pathway_card_ids, + ) + return [] + + +def _is_v3_generic_item(value: str) -> bool: + text = value.strip() + if not text: + return False + return any(pattern.search(text) for pattern in V3_GENERIC_OUTPUT_PATTERNS) + + +def _is_v5_generic_observation_item(value: str) -> bool: + text = value.strip() + if not text: + return False + return any(pattern.search(text) for pattern in V5_GENERIC_OBSERVATION_PATTERNS) + + +def _normalized_list(values: list[str]) -> list[str]: + return [_normalize_text(value) for value in values if _normalize_text(value)] + + +def _has_v6_harness_metadata_cue(value: str) -> bool: + normalized = _normalize_text(value) + return any(_normalize_text(cue) in normalized for cue in V6_HARNESS_METADATA_OBSERVATION_CUES) + + +def _observation_text_has_unsafe_instruction(value: str) -> bool: + return any(pattern.search(value) for pattern in V2_FORBIDDEN_LEXICAL_PATTERNS.values()) + + +def _required_observation_target_visible( + target: dict[str, Any], + text: str, + tokens: set[str], + *, + structured_intake: dict[str, Any] | None = None, +) -> bool: + cue_tokens = {str(token) for token in target.get("cue_tokens", []) if str(token)} + if cue_tokens and cue_tokens <= tokens: + return True + display_text = str(target.get("display_text") or "") + normalized_display = _normalize_text(display_text) + normalized_text = _normalize_text(text) + if normalized_display and normalized_display in normalized_text: + return True + resource_aware_text = _v3_resource_aware_cue_text(display_text, structured_intake or {}) + normalized_resource_aware = _normalize_text(resource_aware_text) + return bool(normalized_resource_aware and normalized_resource_aware in normalized_text) + + +def _resource_unavailable(resource_text: str, phrases: tuple[str, ...]) -> bool: + return any(phrase in resource_text for phrase in phrases) + + +def _asks_for_unavailable_pulse_ox(output_text: str) -> bool: + if "unavailable" in output_text and any( + phrase in output_text for phrase in ("pulse ox", "pulse oximeter", "oxygen saturation", "spo2") + ): + return False + return any(phrase in output_text for phrase in ("pulse ox", "pulse oximeter", "oxygen saturation", "spo2", "repeat vitals")) + + +def _asks_for_unavailable_bp(output_text: str) -> bool: + if "unavailable" in output_text and any(phrase in output_text for phrase in ("blood pressure", "bp cuff", "bp")): + return False + return any(phrase in output_text for phrase in ("blood pressure", "bp cuff", "repeat vitals")) + + +def eval_record_for_output( + prepared: PreparedCase, + output: dict[str, Any], + validation: dict[str, Any], +) -> dict[str, Any]: + cue_buckets = bucket_expected_observation_cues(prepared.expected_missing_observations) + harness_evidence = build_harness_evidence( + confirmed_intake=prepared.spec.structured_intake, + retrieved_card_ids=prepared.retrieved_ids, + rule_results=prepared.rule_results, + urgency_floor=prepared.urgency_floor, + validator_result=validation, + final_output=output, + ) + return { + "case_id": prepared.spec.case_id, + "structured_intake": prepared.spec.structured_intake, + "target_protocol_card_id": prepared.spec.target_protocol_card_id, + "expected_min_protocol_urgency": prepared.urgency_floor, + "expected_red_flag_rule_ids": prepared.expected_red_flag_rule_ids, + "expected_source_card_ids": prepared.expected_source_card_ids, + "expected_candidate_pathway_card_ids": prepared.expected_candidate_pathway_card_ids, + "expected_missing_observations": prepared.expected_missing_observations, + "expected_model_observation_cues": cue_buckets["model"], + "expected_handoff_cues": cue_buckets["handoff"], + "expected_harness_evidence_cues": cue_buckets["harness"], + "forbidden_behavior": forbidden_behavior_for_version(prepared.spec.dataset_version), + "actual_red_flag_rule_ids": [str(rule["rule_id"]) for rule in prepared.rule_results], + "actual_protocol_urgency": output.get("protocol_urgency"), + "actual_source_card_ids": _string_list(output.get("source_cards")), + "actual_candidate_pathway_card_ids": _candidate_ids(output.get("candidate_protocol_pathways")), + "retrieved_card_ids": prepared.retrieved_ids, + "harness_evidence": harness_evidence, + "final_output": output, + "final_validation": validation, + } + + +def build_sft_row( + *, + prepared: PreparedCase, + result: CandidateResult, + teacher_model_id: str, + candidate_total: int, + candidate_passed: int, +) -> dict[str, Any]: + workflow_category = str(prepared.spec.structured_intake.get("workflow_category") or "") + cue_buckets = bucket_expected_observation_cues(prepared.expected_missing_observations) + metadata = { + "teacher_model_id": teacher_model_id, + "critic_model_id": teacher_model_id, + "teacher_label_mode": "streamed_ultra_semantic_notes_harness_prompt", + "teacher_base_url_env": _endpoint_env_name(teacher_model_id), + "teacher_api_key_env": _api_key_env_name(teacher_model_id), + "failure_class": prepared.spec.failure_class, + "dataset_version": prepared.spec.dataset_version, + "expected_action": { + "target_card": prepared.spec.target_protocol_card_id, + "source_cards": prepared.expected_source_card_ids, + "candidate_pathway_card_ids": prepared.expected_candidate_pathway_card_ids, + "required_observation_cues": prepared.expected_missing_observations, + "model_observation_cues": cue_buckets["model"], + "handoff_cues": cue_buckets["handoff"], + "harness_evidence_cues": cue_buckets["harness"], + "red_flag_rule_ids": prepared.expected_red_flag_rule_ids, + "min_protocol_urgency": prepared.urgency_floor, + }, + "reward_components": result.reward_components, + "pass_rate_total": candidate_total, + "pass_rate_passed": candidate_passed, + "dedupe_hash": dedupe_hash(prepared), + "input_hash": stable_hash(prepared.spec.structured_intake), + "prompt_hash": stable_hash(prepared.prompt), + "prompt_template_hash": prepared.prompt_hash, + "raw_teacher_output_hash": result.raw_output_hash, + "deterministic_scaffold_patched_fields": result.patched_fields, + "filled_required_observation_ids": result.filled_required_observation_ids, + "model_selected_required_observation_ids": result.model_selected_required_observation_ids, + "invalid_selected_required_observation_ids": result.invalid_selected_required_observation_ids, + "stripped_trace_only_fields": result.stripped_trace_only_fields, + "validation_result": result.validation, + "expected_label_score": result.expected_label_score, + "retrieved_card_ids": prepared.retrieved_ids, + "recipe_sources": [ + "nvidia/Nemotron-Post-Training-Dataset-v2", + "nvidia/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1", + "nvidia/Nemotron-CC-v2", + ], + "validator_passed": True, + "license_review": "synthetic_figment_row_no_nvidia_rows_copied", + "phi_status": "synthetic_deidentified_no_phi", + "generated_at": datetime.now(UTC).isoformat(), + } + if workflow_category: + metadata.update( + { + "workflow_category": workflow_category, + "field_workflow_goal": prepared.spec.structured_intake.get("field_workflow_goal"), + "workflow_priority_observations": prepared.expected_missing_observations[:5], + "v3_workflow_validator_version": 1, + "anti_overfit_policy": { + "locked_eval_copying_allowed": False, + "holdout_copying_allowed": False, + "primary_success_surface": "field_workflow_holdout_v1", + }, + } + ) + if uses_v5_focused_policy(prepared.spec.dataset_version): + must_include_selected = v5_required_selected_observation_ids( + source_card_ids=_string_list(result.output.get("source_cards")), + retrieved_cards=prepared.retrieved_cards, + ) + metadata.update( + { + "training_focus": prepared.spec.failure_class, + "v5_training_policy_version": 1, + "excluded_eval_case_ids": list(V5_EXCLUDED_EVAL_CASE_IDS), + "must_include_source_cards": _v5_must_include_source_cards(prepared), + "must_include_selected_required_observation_ids": must_include_selected, + } + ) + if uses_v6_observation_policy(prepared.spec.dataset_version): + must_include_selected = required_selected_observation_ids_for_version( + source_card_ids=_string_list(result.output.get("source_cards")), + retrieved_cards=prepared.retrieved_cards, + dataset_version=prepared.spec.dataset_version, + target_protocol_card_id=prepared.spec.target_protocol_card_id, + failure_class=prepared.spec.failure_class, + ) + metadata.update( + { + "training_focus": prepared.spec.failure_class, + "v6_training_policy_version": 1, + "must_include_source_cards": _v5_must_include_source_cards(prepared), + "required_observation_targets": _v6_required_observation_targets(prepared), + "must_include_selected_required_observation_ids": must_include_selected, + "harness_metadata_cues_not_observations": list(V6_HARNESS_METADATA_OBSERVATION_CUES), + "observation_field_contract": { + "missing_info_to_collect": "broader still-needed clinical observations", + "next_observations_to_collect": "prioritized next 3-5 clinical observations", + "selected_required_observation_ids": "trace-only ids; runtime strips from user-visible output", + }, + } + ) + if uses_v7_source_card_policy(prepared.spec.dataset_version): + metadata.update( + { + "v7_training_policy_version": 1, + "source_card_closure_contract": { + "target_protocol_card_id": prepared.spec.target_protocol_card_id, + "must_include_source_cards": _v5_must_include_source_cards(prepared), + "safety_card_required_when_safety_text_present": SAFETY_CARD_ID, + "sbar_card_required_when_handoff_present": SBAR_CARD_ID, + }, + } + ) + return { + "case_id": prepared.spec.case_id, + "uuid": prepared.spec.case_id, + "license": "synthetic internal training data", + "generator": teacher_model_id, + "version": prepared.spec.dataset_version, + "category": prepared.spec.failure_class, + "reasoning": "off", + "messages": [ + {"role": "user", "content": prepared.prompt}, + {"role": "assistant", "content": json.dumps(result.output, sort_keys=True)}, + ], + "tags": prepared.spec.tags, + "metadata": metadata, + } + + +def case_spec_record(prepared: PreparedCase) -> dict[str, Any]: + cue_buckets = bucket_expected_observation_cues(prepared.expected_missing_observations) + record = { + "case_id": prepared.spec.case_id, + "dataset_version": prepared.spec.dataset_version, + "failure_class": prepared.spec.failure_class, + "target_protocol_card_id": prepared.spec.target_protocol_card_id, + "structured_intake": prepared.spec.structured_intake, + "expected_red_flag_rule_ids": prepared.expected_red_flag_rule_ids, + "expected_min_protocol_urgency": prepared.urgency_floor, + "expected_source_card_ids": prepared.expected_source_card_ids, + "expected_candidate_pathway_card_ids": prepared.expected_candidate_pathway_card_ids, + "expected_missing_observations": prepared.expected_missing_observations, + "expected_model_observation_cues": cue_buckets["model"], + "expected_handoff_cues": cue_buckets["handoff"], + "expected_harness_evidence_cues": cue_buckets["harness"], + "retrieved_card_ids": prepared.retrieved_ids, + "tags": prepared.spec.tags, + } + workflow_category = str(prepared.spec.structured_intake.get("workflow_category") or "") + if workflow_category: + record.update( + { + "workflow_category": workflow_category, + "field_workflow_goal": prepared.spec.structured_intake.get("field_workflow_goal"), + "workflow_priority_observations": prepared.expected_missing_observations[:5], + "field_workflow_holdout_relevant": True, + } + ) + if uses_v6_observation_policy(prepared.spec.dataset_version): + record.update( + { + "required_observation_targets": _v6_required_observation_targets(prepared), + "must_include_selected_required_observation_ids": required_selected_observation_ids_for_version( + source_card_ids=prepared.expected_source_card_ids, + retrieved_cards=prepared.retrieved_cards, + dataset_version=prepared.spec.dataset_version, + target_protocol_card_id=prepared.spec.target_protocol_card_id, + failure_class=prepared.spec.failure_class, + ), + "harness_metadata_cues_not_observations": list(V6_HARNESS_METADATA_OBSERVATION_CUES), + } + ) + if uses_v7_source_card_policy(prepared.spec.dataset_version): + record.update( + { + "source_card_closure_contract": { + "target_protocol_card_id": prepared.spec.target_protocol_card_id, + "must_include_source_cards": _v5_must_include_source_cards(prepared), + }, + } + ) + return record + + +def build_manifest( + *, + output_path: Path, + case_specs_path: Path, + dataset_version: str, + rows: list[dict[str, Any]], + started_at: datetime, + teacher_model_id: str, + dry_run: bool, + attempts: int, + start_index: int, + index_stride: int, + counters: Counter[str], + candidate_totals: Counter[str], + rejection_reasons: Counter[str], + events: list[dict[str, Any]], + exclusion_paths: list[Path] | None = None, + exclusion_signature_count: int = 0, +) -> dict[str, Any]: + finished_at = datetime.now(UTC) + return { + "dataset_version": dataset_version, + "row_count": len(rows), + "output_path": str(output_path), + "case_specs_path": str(case_specs_path), + "output_sha256": _file_sha256(output_path) if output_path.exists() else None, + "case_specs_sha256": _file_sha256(case_specs_path) if case_specs_path.exists() else None, + "started_at": started_at.isoformat(), + "finished_at": finished_at.isoformat(), + "elapsed_seconds": round((finished_at - started_at).total_seconds(), 3), + "teacher_model_id": teacher_model_id, + "teacher_endpoint_env": _endpoint_env_name(teacher_model_id), + "teacher_api_key_env": _api_key_env_name(teacher_model_id), + "dry_run": dry_run, + "attempts": attempts, + "start_index": start_index, + "index_stride": index_stride, + "accepted_by_failure_class": { + key: value for key, value in sorted(counters.items()) if not key.startswith("tag:") + }, + "accepted_by_tag": { + key[4:]: value for key, value in sorted(counters.items()) if key.startswith("tag:") + }, + "candidate_totals": dict(candidate_totals), + "rejection_reasons": dict(rejection_reasons), + "anti_overfit_exclusions": { + "enabled": bool(exclusion_paths), + "eval_paths": [str(path) for path in exclusion_paths or []], + "signature_count": exclusion_signature_count, + "policies": [ + "exact clinical-intake hash rejection", + "same target/workflow high-token-overlap rejection", + ], + }, + "source_recipe_links": [ + "nvidia/Nemotron-Post-Training-Dataset-v2", + "nvidia/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1", + "nvidia/Nemotron-CC-v2", + ], + "license_phi_assertions": { + "synthetic_only": True, + "no_phi": True, + "no_locked_eval_rows_copied": True, + "no_nvidia_dataset_rows_copied": True, + "requires_license_review_before_distribution": True, + }, + "prompt_template_hash": stable_hash(SYSTEM_PROMPT), + "event_sample": events[-50:], + } + + +def _load_existing_rows(path: Path) -> list[dict[str, Any]]: + if not path.exists(): + return [] + rows = [] + for line in path.read_text(encoding="utf-8").splitlines(): + if line.strip(): + rows.append(json.loads(line)) + return rows + + +def _rejection_key(result: CandidateResult) -> str: + if result.validation.get("passed") is not True: + failures = result.validation.get("failures") or ["validation_failed"] + return _safe_counter_key(str(failures[0])) + if result.expected_label_score.get("all_expected_labels_passed") is not True: + for key, value in result.expected_label_score.items(): + if value is False: + return f"expected_label_{key}" + return "expected_label_failed" + failed_rewards = [key for key, value in result.reward_components.items() if not value] + return f"reward_{failed_rewards[0]}" if failed_rewards else "unknown" + + +def _patch_fields(before: dict[str, Any], after: dict[str, Any]) -> list[str]: + return sorted(field for field in REQUIRED_JSON_SKELETON if before.get(field) != after.get(field)) + + +def _candidate_ids(value: Any) -> list[str]: + if not isinstance(value, list): + return [] + ids: list[str] = [] + for item in value: + card_id = item.get("card_id") if isinstance(item, dict) else item + if card_id: + ids.append(str(card_id)) + return ids + + +def _string_list(value: Any) -> list[str]: + if isinstance(value, list): + return [str(item) for item in value if str(item)] + if isinstance(value, str) and value.strip(): + return [value.strip()] + return [] + + +def _dedupe(values: list[str]) -> list[str]: + out: list[str] = [] + for value in values: + text = str(value).strip() + if text and text not in out: + out.append(text) + return out + + +def _pick(values: list[str], index: int) -> str: + return values[index % len(values)] + + +def _tag_for_card(card_id: str) -> str: + return card_id.lower().replace("-v1", "").replace("-", "_") + + +def dedupe_hash(prepared: PreparedCase) -> str: + payload = { + "normalized_intake": _normalize_text(json.dumps(prepared.spec.structured_intake, sort_keys=True)), + "target": prepared.spec.target_protocol_card_id, + "expected_source": prepared.expected_source_card_ids, + "expected_missing": prepared.expected_missing_observations, + } + return "sha256:" + hashlib.sha256(json.dumps(payload, sort_keys=True).encode("utf-8")).hexdigest() + + +def _normalize_text(value: str) -> str: + return " ".join(re.findall(r"[a-z0-9]+", value.lower())) + + +def _endpoint_env_name(teacher_model_id: str | None = None) -> str: + # Record only the variable name, never the resolved endpoint or secret. + if teacher_model_id and _openrouter_config_for_teacher_model(teacher_model_id): + return "OPENROUTER_BASE_URL" + if os.getenv("OMNI_ENDPOINT_URL", "").strip(): + return "OMNI_ENDPOINT_URL" + if os.getenv("HF_ENDPOINT_URL", "").strip(): + return "HF_ENDPOINT_URL" + if os.getenv("NVIDIA_BASE_URL", "").strip(): + return "NVIDIA_BASE_URL" + return f"NVIDIA_BASE_URL(default:{NVIDIA_API_BASE_URL})" + + +def _api_key_env_name(teacher_model_id: str | None = None) -> str: + # Record only the variable name, never the resolved secret. + if teacher_model_id and _openrouter_config_for_teacher_model(teacher_model_id): + return "OPENROUTER_API_KEY" + if os.getenv("OMNI_ENDPOINT_URL", "").strip() or os.getenv("HF_ENDPOINT_URL", "").strip(): + return "HF_TOKEN" if os.getenv("HF_TOKEN", "").strip() else "" + if os.getenv("NVIDIA_API_KEY", "").strip(): + return "NVIDIA_API_KEY" + return "" + + +def _file_sha256(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as file: + for chunk in iter(lambda: file.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +def _print_progress_event(event: dict[str, Any]) -> None: + print(json.dumps(event, sort_keys=True), flush=True) + + +def _safe_counter_key(value: str) -> str: + return re.sub(r"[^a-z0-9_.:-]+", "_", value.lower()).strip("_")[:120] or "unknown" + + +def _safe_error_text(value: str) -> str: + text = re.sub(r"(?i)bearer\s+[^\s]+", "Bearer [redacted]", value) + text = re.sub(r"(?i)(api_key|token|authorization)=([^&\s]+)", r"\1=[redacted]", text) + return text[:500] + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_v10_full_corpus.py b/scripts/generate_v10_full_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..e7eeae8a676b1d96d88bec074999115d5adc2b6d --- /dev/null +++ b/scripts/generate_v10_full_corpus.py @@ -0,0 +1,66 @@ +"""Generate, verify, and Modal-prep the Figment v10 delta SFT corpus.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.generate_finetune_data import V10_NAVIGATOR_COUNTS # noqa: E402 +from scripts.generate_v3_full_corpus import main as _run_full_corpus # noqa: E402 + + +DEFAULT_OUTPUT_VERSION = "figment_sft_v10_delta" +DEFAULT_TEACHER_MODEL_ID = "nvidia/nemotron-3-ultra-550b-a55b:free" +DEFAULT_NAVIGATOR_COUNT = sum(V10_NAVIGATOR_COUNTS.values()) +DEFAULT_REPAIR_COUNT = 0 +DEFAULT_ARGS = [ + "--dataset-version", + DEFAULT_OUTPUT_VERSION, + "--navigator-count", + str(DEFAULT_NAVIGATOR_COUNT), + "--repair-count", + str(DEFAULT_REPAIR_COUNT), + "--teacher-model-id", + DEFAULT_TEACHER_MODEL_ID, + "--base-start-index", + "120000", + "--rows-per-shard", + "40", + "--shard-prefix", + "data/finetune/shards/figment_sft_v10_delta_full_shard", + "--output", + "data/finetune/figment_sft_v10_delta.jsonl", + "--case-specs", + "data/finetune/figment_sft_v10_delta_case_specs.jsonl", + "--manifest", + "data/finetune/figment_sft_v10_delta_manifest.json", + "--modal-output-dir", + "data/finetune/modal/figment_sft_v10_delta", + "--seed", + "figment-modal-sft-v10-delta", +] + + +def build_corpus_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--navigator-count", type=int, default=DEFAULT_NAVIGATOR_COUNT) + parser.add_argument("--repair-count", type=int, default=DEFAULT_REPAIR_COUNT) + parsed, remaining = parser.parse_known_args(raw_args) + defaults = list(DEFAULT_ARGS) + defaults[defaults.index("--navigator-count") + 1] = str(parsed.navigator_count) + defaults[defaults.index("--repair-count") + 1] = str(parsed.repair_count) + return defaults + remaining + + +def main(argv: list[str] | None = None) -> int: + return _run_full_corpus(build_corpus_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_v11_full_corpus.py b/scripts/generate_v11_full_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..d8c68002e0c62b69d9dbcbc675f268470bc37b71 --- /dev/null +++ b/scripts/generate_v11_full_corpus.py @@ -0,0 +1,66 @@ +"""Generate, verify, and Modal-prep the Figment v11 delta SFT corpus.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.generate_finetune_data import V11_NAVIGATOR_COUNTS # noqa: E402 +from scripts.generate_v3_full_corpus import main as _run_full_corpus # noqa: E402 + + +DEFAULT_OUTPUT_VERSION = "figment_sft_v11_delta" +DEFAULT_TEACHER_MODEL_ID = "nvidia/nemotron-3-ultra-550b-a55b:free" +DEFAULT_NAVIGATOR_COUNT = sum(V11_NAVIGATOR_COUNTS.values()) +DEFAULT_REPAIR_COUNT = 0 +DEFAULT_ARGS = [ + "--dataset-version", + DEFAULT_OUTPUT_VERSION, + "--navigator-count", + str(DEFAULT_NAVIGATOR_COUNT), + "--repair-count", + str(DEFAULT_REPAIR_COUNT), + "--teacher-model-id", + DEFAULT_TEACHER_MODEL_ID, + "--base-start-index", + "140000", + "--rows-per-shard", + "40", + "--shard-prefix", + "data/finetune/shards/figment_sft_v11_delta_full_shard", + "--output", + "data/finetune/figment_sft_v11_delta.jsonl", + "--case-specs", + "data/finetune/figment_sft_v11_delta_case_specs.jsonl", + "--manifest", + "data/finetune/figment_sft_v11_delta_manifest.json", + "--modal-output-dir", + "data/finetune/modal/figment_sft_v11_delta", + "--seed", + "figment-modal-sft-v11-delta", +] + + +def build_corpus_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--navigator-count", type=int, default=DEFAULT_NAVIGATOR_COUNT) + parser.add_argument("--repair-count", type=int, default=DEFAULT_REPAIR_COUNT) + parsed, remaining = parser.parse_known_args(raw_args) + defaults = list(DEFAULT_ARGS) + defaults[defaults.index("--navigator-count") + 1] = str(parsed.navigator_count) + defaults[defaults.index("--repair-count") + 1] = str(parsed.repair_count) + return defaults + remaining + + +def main(argv: list[str] | None = None) -> int: + return _run_full_corpus(build_corpus_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_v12_full_corpus.py b/scripts/generate_v12_full_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..c962319ee292fd3bfd8f3833873a791ae8d4d401 --- /dev/null +++ b/scripts/generate_v12_full_corpus.py @@ -0,0 +1,66 @@ +"""Generate, verify, and Modal-prep the Figment v12 delta SFT corpus.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.generate_finetune_data import V12_NAVIGATOR_COUNTS # noqa: E402 +from scripts.generate_v3_full_corpus import main as _run_full_corpus # noqa: E402 + + +DEFAULT_OUTPUT_VERSION = "figment_sft_v12_delta" +DEFAULT_TEACHER_MODEL_ID = "nvidia/nemotron-3-ultra-550b-a55b:free" +DEFAULT_NAVIGATOR_COUNT = sum(V12_NAVIGATOR_COUNTS.values()) +DEFAULT_REPAIR_COUNT = 0 +DEFAULT_ARGS = [ + "--dataset-version", + DEFAULT_OUTPUT_VERSION, + "--navigator-count", + str(DEFAULT_NAVIGATOR_COUNT), + "--repair-count", + str(DEFAULT_REPAIR_COUNT), + "--teacher-model-id", + DEFAULT_TEACHER_MODEL_ID, + "--base-start-index", + "160000", + "--rows-per-shard", + "40", + "--shard-prefix", + "data/finetune/shards/figment_sft_v12_delta_full_shard", + "--output", + "data/finetune/figment_sft_v12_delta.jsonl", + "--case-specs", + "data/finetune/figment_sft_v12_delta_case_specs.jsonl", + "--manifest", + "data/finetune/figment_sft_v12_delta_manifest.json", + "--modal-output-dir", + "data/finetune/modal/figment_sft_v12_delta", + "--seed", + "figment-modal-sft-v12-delta", +] + + +def build_corpus_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--navigator-count", type=int, default=DEFAULT_NAVIGATOR_COUNT) + parser.add_argument("--repair-count", type=int, default=DEFAULT_REPAIR_COUNT) + parsed, remaining = parser.parse_known_args(raw_args) + defaults = list(DEFAULT_ARGS) + defaults[defaults.index("--navigator-count") + 1] = str(parsed.navigator_count) + defaults[defaults.index("--repair-count") + 1] = str(parsed.repair_count) + return defaults + remaining + + +def main(argv: list[str] | None = None) -> int: + return _run_full_corpus(build_corpus_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_v13_full_corpus.py b/scripts/generate_v13_full_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..bd96768d8e32292bafdbe290b5c0b162d3fe570f --- /dev/null +++ b/scripts/generate_v13_full_corpus.py @@ -0,0 +1,75 @@ +"""Generate, verify, and Modal-prep the Figment v13 delta SFT corpus.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.generate_finetune_data import V13_NAVIGATOR_COUNTS # noqa: E402 +from scripts.generate_v3_full_corpus import main as _run_full_corpus # noqa: E402 + + +DEFAULT_OUTPUT_VERSION = "figment_sft_v13_delta" +DEFAULT_TEACHER_MODEL_ID = "nvidia/nemotron-3-ultra-550b-a55b" +DEFAULT_NAVIGATOR_COUNT = sum(V13_NAVIGATOR_COUNTS.values()) +DEFAULT_REPAIR_COUNT = 0 +DEFAULT_ARGS = [ + "--dataset-version", + DEFAULT_OUTPUT_VERSION, + "--navigator-count", + str(DEFAULT_NAVIGATOR_COUNT), + "--repair-count", + str(DEFAULT_REPAIR_COUNT), + "--teacher-model-id", + DEFAULT_TEACHER_MODEL_ID, + "--no-teacher-worker", + "--base-start-index", + "180000", + "--rows-per-shard", + "10", + "--parallelism", + "2", + "--timeout-seconds", + "120", + "--teacher-error-retries", + "12", + "--teacher-error-sleep-seconds", + "20", + "--shard-prefix", + "data/finetune/shards/figment_sft_v13_delta_full_shard", + "--output", + "data/finetune/figment_sft_v13_delta.jsonl", + "--case-specs", + "data/finetune/figment_sft_v13_delta_case_specs.jsonl", + "--manifest", + "data/finetune/figment_sft_v13_delta_manifest.json", + "--modal-output-dir", + "data/finetune/modal/figment_sft_v13_delta", + "--seed", + "figment-modal-sft-v13-delta", +] + + +def build_corpus_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--navigator-count", type=int, default=DEFAULT_NAVIGATOR_COUNT) + parser.add_argument("--repair-count", type=int, default=DEFAULT_REPAIR_COUNT) + parsed, remaining = parser.parse_known_args(raw_args) + defaults = list(DEFAULT_ARGS) + defaults[defaults.index("--navigator-count") + 1] = str(parsed.navigator_count) + defaults[defaults.index("--repair-count") + 1] = str(parsed.repair_count) + return defaults + remaining + + +def main(argv: list[str] | None = None) -> int: + return _run_full_corpus(build_corpus_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_v14_full_corpus.py b/scripts/generate_v14_full_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..3ff2447d70488980d31a37ed2760f3773c7f437d --- /dev/null +++ b/scripts/generate_v14_full_corpus.py @@ -0,0 +1,75 @@ +"""Generate, verify, and Modal-prep the Figment v14 delta SFT corpus.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.generate_finetune_data import V14_NAVIGATOR_COUNTS # noqa: E402 +from scripts.generate_v3_full_corpus import main as _run_full_corpus # noqa: E402 + + +DEFAULT_OUTPUT_VERSION = "figment_sft_v14_delta" +DEFAULT_TEACHER_MODEL_ID = "nvidia/nemotron-3-ultra-550b-a55b" +DEFAULT_NAVIGATOR_COUNT = sum(V14_NAVIGATOR_COUNTS.values()) +DEFAULT_REPAIR_COUNT = 0 +DEFAULT_ARGS = [ + "--dataset-version", + DEFAULT_OUTPUT_VERSION, + "--navigator-count", + str(DEFAULT_NAVIGATOR_COUNT), + "--repair-count", + str(DEFAULT_REPAIR_COUNT), + "--teacher-model-id", + DEFAULT_TEACHER_MODEL_ID, + "--no-teacher-worker", + "--base-start-index", + "240000", + "--rows-per-shard", + "10", + "--parallelism", + "2", + "--timeout-seconds", + "120", + "--teacher-error-retries", + "20", + "--teacher-error-sleep-seconds", + "20", + "--shard-prefix", + "data/finetune/shards/figment_sft_v14_delta_full_shard", + "--output", + "data/finetune/figment_sft_v14_delta.jsonl", + "--case-specs", + "data/finetune/figment_sft_v14_delta_case_specs.jsonl", + "--manifest", + "data/finetune/figment_sft_v14_delta_manifest.json", + "--modal-output-dir", + "data/finetune/modal/figment_sft_v14_delta", + "--seed", + "figment-modal-sft-v14-delta", +] + + +def build_corpus_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--navigator-count", type=int, default=DEFAULT_NAVIGATOR_COUNT) + parser.add_argument("--repair-count", type=int, default=DEFAULT_REPAIR_COUNT) + parsed, remaining = parser.parse_known_args(raw_args) + defaults = list(DEFAULT_ARGS) + defaults[defaults.index("--navigator-count") + 1] = str(parsed.navigator_count) + defaults[defaults.index("--repair-count") + 1] = str(parsed.repair_count) + return defaults + remaining + + +def main(argv: list[str] | None = None) -> int: + return _run_full_corpus(build_corpus_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_v3_full_corpus.py b/scripts/generate_v3_full_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..df7688f3e7e6bd289599c98e2eedaade7c01b89c --- /dev/null +++ b/scripts/generate_v3_full_corpus.py @@ -0,0 +1,303 @@ +"""Generate, merge, verify, and Modal-prep the full Figment v3 SFT corpus.""" + +from __future__ import annotations + +import argparse +from concurrent.futures import ThreadPoolExecutor +from concurrent.futures import as_completed +from dataclasses import dataclass +import json +import math +from pathlib import Path +import subprocess +import sys +from typing import Any + + +DATASET_VERSION = "figment_sft_v3" +DEFAULT_SHARD_PREFIX = Path("data/finetune/shards/figment_sft_v3_full_shard") +DEFAULT_OUTPUT = Path("data/finetune/figment_sft_v3.jsonl") +DEFAULT_CASE_SPECS = Path("data/finetune/figment_sft_v3_case_specs.jsonl") +DEFAULT_MANIFEST = Path("data/finetune/figment_sft_v3_manifest.json") +DEFAULT_MODAL_DIR = Path("data/finetune/modal/figment_sft_v3") +DEFAULT_TEACHER_MODEL = "nvidia/nemotron-3-ultra-550b-a55b" + + +@dataclass(frozen=True) +class ShardSpec: + index: int + row_count: int + start_index: int + index_stride: int + output: Path + case_specs: Path + manifest: Path + log: Path + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--dataset-version", default=DATASET_VERSION) + parser.add_argument("--navigator-count", type=int, default=2500) + parser.add_argument("--repair-count", type=int, default=500) + parser.add_argument("--rows-per-shard", type=int, default=50) + parser.add_argument("--parallelism", type=int, default=4) + parser.add_argument("--base-start-index", type=int, default=20000) + parser.add_argument("--shard-prefix", type=Path, default=DEFAULT_SHARD_PREFIX) + parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT) + parser.add_argument("--case-specs", type=Path, default=DEFAULT_CASE_SPECS) + parser.add_argument("--manifest", type=Path, default=DEFAULT_MANIFEST) + parser.add_argument("--modal-output-dir", type=Path, default=DEFAULT_MODAL_DIR) + parser.add_argument("--teacher-model-id", default=DEFAULT_TEACHER_MODEL) + parser.add_argument("--timeout-seconds", type=float, default=60.0) + parser.add_argument("--teacher-max-tokens", type=int, default=700) + parser.add_argument("--teacher-error-retries", type=int, default=2) + parser.add_argument("--teacher-error-sleep-seconds", type=float, default=2.0) + parser.add_argument("--no-teacher-worker", action="store_true") + parser.add_argument("--max-attempts-multiplier", type=int, default=8) + parser.add_argument("--validation-fraction", type=float, default=0.1) + parser.add_argument("--seed", default="figment-modal-sft-v3") + parser.add_argument("--min-validation-group-size", type=int, default=5) + parser.add_argument("--skip-generation", action="store_true") + parser.add_argument("--skip-repair", action="store_true") + parser.add_argument("--only-generate", action="store_true") + parser.add_argument("--log-rejections", action="store_true") + parser.add_argument("--dry-run", action="store_true", help="Use deterministic fallback rows instead of teacher calls.") + args = parser.parse_args(argv) + + if args.navigator_count <= 0: + raise SystemExit("--navigator-count must be positive") + if args.repair_count < 0: + raise SystemExit("--repair-count must be non-negative") + if args.rows_per_shard <= 0: + raise SystemExit("--rows-per-shard must be positive") + if args.parallelism <= 0: + raise SystemExit("--parallelism must be positive") + if args.max_attempts_multiplier < 1: + raise SystemExit("--max-attempts-multiplier must be at least 1") + + shard_specs = build_shard_specs( + navigator_count=args.navigator_count, + rows_per_shard=args.rows_per_shard, + base_start_index=args.base_start_index, + shard_prefix=args.shard_prefix, + ) + generation_results = [] + if not args.skip_generation: + generation_results = generate_shards(args, shard_specs) + + if args.only_generate: + print(json.dumps({"shards": [spec.__dict__ | {"output": str(spec.output)} for spec in shard_specs]}, default=str)) + return 0 + + merge_cmd = [ + sys.executable, + "scripts/merge_finetune_shards.py", + "--dataset-version", + args.dataset_version, + "--shard-prefix", + str(args.shard_prefix), + "--shard-count", + str(len(shard_specs)), + "--output", + str(args.output), + "--case-specs", + str(args.case_specs), + "--manifest", + str(args.manifest), + ] + merge_summary = _run_json_command(merge_cmd) + + repair_summary = None + if not args.skip_repair and args.repair_count: + repair_summary = _run_json_command(build_repair_command(args)) + + verify_summary = _run_json_command( + [ + sys.executable, + "scripts/verify_finetune_harness_alignment.py", + "--dataset", + str(args.output), + "--case-specs", + str(args.case_specs), + ] + ) + if verify_summary.get("passed") is not True: + raise SystemExit(f"harness verification failed: {json.dumps(verify_summary, sort_keys=True)}") + + modal_summary = _run_json_command( + [ + sys.executable, + "scripts/prepare_modal_finetune_dataset.py", + "--dataset", + str(args.output), + "--dataset-version", + args.dataset_version, + "--output-dir", + str(args.modal_output_dir), + "--validation-fraction", + str(args.validation_fraction), + "--seed", + args.seed, + "--min-validation-group-size", + str(args.min_validation_group_size), + ] + ) + + summary = { + "dataset_version": args.dataset_version, + "navigator_count": args.navigator_count, + "repair_count": args.repair_count, + "shard_count": len(shard_specs), + "generation": generation_results, + "merge": merge_summary, + "repair": repair_summary, + "verify": verify_summary, + "modal": modal_summary, + } + print(json.dumps(summary, indent=2, sort_keys=True, default=str)) + return 0 + + +def build_shard_specs( + *, + navigator_count: int, + rows_per_shard: int, + base_start_index: int, + shard_prefix: Path, +) -> list[ShardSpec]: + shard_count = math.ceil(navigator_count / rows_per_shard) + specs: list[ShardSpec] = [] + remaining = navigator_count + for index in range(shard_count): + row_count = min(rows_per_shard, remaining) + base = Path(f"{shard_prefix}{index}") + specs.append( + ShardSpec( + index=index, + row_count=row_count, + start_index=base_start_index + index, + index_stride=shard_count, + output=Path(f"{base}.jsonl"), + case_specs=Path(f"{base}_case_specs.jsonl"), + manifest=Path(f"{base}_manifest.json"), + log=Path(f"{base}.log"), + ) + ) + remaining -= row_count + return specs + + +def generate_shards(args: argparse.Namespace, shard_specs: list[ShardSpec]) -> list[dict[str, Any]]: + for spec in shard_specs: + spec.output.parent.mkdir(parents=True, exist_ok=True) + results: list[dict[str, Any]] = [] + with ThreadPoolExecutor(max_workers=args.parallelism) as executor: + futures = [executor.submit(generate_one_shard, args, spec) for spec in shard_specs] + for future in as_completed(futures): + result = future.result() + results.append(result) + print(json.dumps({"shard_complete": result}, sort_keys=True), flush=True) + return sorted(results, key=lambda item: int(item["index"])) + + +def generate_one_shard(args: argparse.Namespace, spec: ShardSpec) -> dict[str, Any]: + existing = _read_manifest(spec.manifest) + if existing and int(existing.get("row_count") or 0) >= spec.row_count: + return {"index": spec.index, "status": "skipped_existing", "rows": int(existing.get("row_count") or 0)} + + cmd = [ + sys.executable, + "scripts/generate_finetune_data.py", + "--dataset-version", + args.dataset_version, + "--count", + str(spec.row_count), + "--output", + str(spec.output), + "--case-specs", + str(spec.case_specs), + "--manifest", + str(spec.manifest), + "--teacher-model-id", + args.teacher_model_id, + "--timeout-seconds", + str(args.timeout_seconds), + "--teacher-max-tokens", + str(args.teacher_max_tokens), + "--teacher-error-retries", + str(args.teacher_error_retries), + "--teacher-error-sleep-seconds", + str(args.teacher_error_sleep_seconds), + "--candidate-count", + "1", + "--high-risk-candidate-count", + "1", + "--max-attempts", + str(spec.row_count * args.max_attempts_multiplier), + "--start-index", + str(spec.start_index), + "--index-stride", + str(spec.index_stride), + "--resume", + ] + if args.log_rejections: + cmd.append("--log-rejections") + if args.dry_run: + cmd.append("--dry-run") + if args.no_teacher_worker: + cmd.append("--no-teacher-worker") + + spec.log.parent.mkdir(parents=True, exist_ok=True) + with spec.log.open("a", encoding="utf-8") as log: + log.write("\n=== command ===\n") + log.write(" ".join(cmd) + "\n") + log.flush() + completed = subprocess.run(cmd, stdout=log, stderr=subprocess.STDOUT, text=True) + if completed.returncode != 0: + raise RuntimeError(f"shard {spec.index} failed with exit {completed.returncode}; see {spec.log}") + manifest = _read_manifest(spec.manifest) + return { + "index": spec.index, + "status": "generated", + "rows": int(manifest.get("row_count") or 0), + "attempts": int(manifest.get("attempts") or 0), + "manifest": str(spec.manifest), + "log": str(spec.log), + } + + +def build_repair_command(args: argparse.Namespace) -> list[str]: + return [ + sys.executable, + "scripts/augment_finetune_repair_rows.py", + "--dataset-version", + args.dataset_version, + "--dataset", + str(args.output), + "--case-specs", + str(args.case_specs), + "--manifest", + str(args.manifest), + "--repair-count", + str(args.repair_count), + ] + + +def _read_manifest(path: Path) -> dict[str, Any]: + if not path.exists(): + return {} + try: + data = json.loads(path.read_text(encoding="utf-8")) + except json.JSONDecodeError: + return {} + return data if isinstance(data, dict) else {} + + +def _run_json_command(cmd: list[str]) -> dict[str, Any]: + completed = subprocess.run(cmd, check=True, text=True, capture_output=True) + return json.loads(completed.stdout) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_v4_full_corpus.py b/scripts/generate_v4_full_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..51538d805a1b20bcbb97227aae2fb26b6071a71d --- /dev/null +++ b/scripts/generate_v4_full_corpus.py @@ -0,0 +1,48 @@ +"""Generate, verify, and Modal-prep the full Figment v4 SFT corpus.""" + +from __future__ import annotations + +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.generate_v3_full_corpus import main as _run_full_corpus # noqa: E402 + + +DEFAULT_ARGS = [ + "--dataset-version", + "figment_sft_v4", + "--navigator-count", + "1500", + "--repair-count", + "150", + "--base-start-index", + "40000", + "--shard-prefix", + "data/finetune/shards/figment_sft_v4_full_shard", + "--output", + "data/finetune/figment_sft_v4.jsonl", + "--case-specs", + "data/finetune/figment_sft_v4_case_specs.jsonl", + "--manifest", + "data/finetune/figment_sft_v4_manifest.json", + "--modal-output-dir", + "data/finetune/modal/figment_sft_v4", + "--seed", + "figment-modal-sft-v4", +] + + +def build_corpus_args(argv: list[str] | None = None) -> list[str]: + return DEFAULT_ARGS + list(sys.argv[1:] if argv is None else argv) + + +def main(argv: list[str] | None = None) -> int: + return _run_full_corpus(build_corpus_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_v5_full_corpus.py b/scripts/generate_v5_full_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..090164a100ab3a61cce41548ab65ca3b030f7265 --- /dev/null +++ b/scripts/generate_v5_full_corpus.py @@ -0,0 +1,56 @@ +"""Generate, verify, and Modal-prep the full Figment v5 SFT corpus.""" + +from __future__ import annotations + +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.generate_finetune_data import V5_FOCUSED_COUNTS # noqa: E402 +from scripts.generate_v3_full_corpus import main as _run_full_corpus # noqa: E402 + + +DEFAULT_OUTPUT_VERSION = "figment_sft_v5" +DEFAULT_TEACHER_MODEL_ID = "nvidia/nemotron-3-ultra-550b-a55b:free" +DEFAULT_COUNTS = dict(V5_FOCUSED_COUNTS) +DEFAULT_NAVIGATOR_COUNT = sum(DEFAULT_COUNTS.values()) + +DEFAULT_ARGS = [ + "--dataset-version", + DEFAULT_OUTPUT_VERSION, + "--navigator-count", + str(DEFAULT_NAVIGATOR_COUNT), + "--repair-count", + "200", + "--teacher-model-id", + DEFAULT_TEACHER_MODEL_ID, + "--base-start-index", + "60000", + "--shard-prefix", + "data/finetune/shards/figment_sft_v5_full_shard", + "--output", + "data/finetune/figment_sft_v5.jsonl", + "--case-specs", + "data/finetune/figment_sft_v5_case_specs.jsonl", + "--manifest", + "data/finetune/figment_sft_v5_manifest.json", + "--modal-output-dir", + "data/finetune/modal/figment_sft_v5", + "--seed", + "figment-modal-sft-v5", +] + + +def build_corpus_args(argv: list[str] | None = None) -> list[str]: + return DEFAULT_ARGS + list(sys.argv[1:] if argv is None else argv) + + +def main(argv: list[str] | None = None) -> int: + return _run_full_corpus(build_corpus_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_v6_full_corpus.py b/scripts/generate_v6_full_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..e88d5aa5e7b7d7779106bb04b2944055d25edcf2 --- /dev/null +++ b/scripts/generate_v6_full_corpus.py @@ -0,0 +1,66 @@ +"""Generate, verify, and Modal-prep the Figment v6 delta SFT corpus.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.generate_finetune_data import V6_NAVIGATOR_COUNTS # noqa: E402 +from scripts.generate_v3_full_corpus import main as _run_full_corpus # noqa: E402 + + +DEFAULT_OUTPUT_VERSION = "figment_sft_v6_delta" +DEFAULT_TEACHER_MODEL_ID = "nvidia/nemotron-3-ultra-550b-a55b:free" +DEFAULT_NAVIGATOR_COUNT = sum(V6_NAVIGATOR_COUNTS.values()) +DEFAULT_REPAIR_COUNT = 250 +DEFAULT_ARGS = [ + "--dataset-version", + DEFAULT_OUTPUT_VERSION, + "--navigator-count", + str(DEFAULT_NAVIGATOR_COUNT), + "--repair-count", + str(DEFAULT_REPAIR_COUNT), + "--teacher-model-id", + DEFAULT_TEACHER_MODEL_ID, + "--base-start-index", + "70000", + "--shard-prefix", + "data/finetune/shards/figment_sft_v6_delta_full_shard", + "--output", + "data/finetune/figment_sft_v6_delta.jsonl", + "--case-specs", + "data/finetune/figment_sft_v6_delta_case_specs.jsonl", + "--manifest", + "data/finetune/figment_sft_v6_delta_manifest.json", + "--modal-output-dir", + "data/finetune/modal/figment_sft_v6_delta", + "--seed", + "figment-modal-sft-v6-delta", +] + + +def build_corpus_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--new-delta-count", type=int, default=1000) + parser.add_argument("--correction-count", type=int, default=180) + parser.add_argument("--repair-count", type=int, default=DEFAULT_REPAIR_COUNT) + parsed, remaining = parser.parse_known_args(raw_args) + navigator_count = parsed.new_delta_count + parsed.correction_count + defaults = list(DEFAULT_ARGS) + defaults[defaults.index("--navigator-count") + 1] = str(navigator_count) + defaults[defaults.index("--repair-count") + 1] = str(parsed.repair_count) + return defaults + remaining + + +def main(argv: list[str] | None = None) -> int: + return _run_full_corpus(build_corpus_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_v7_full_corpus.py b/scripts/generate_v7_full_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..ce611033c503859f447a7b94142c61368a4b378d --- /dev/null +++ b/scripts/generate_v7_full_corpus.py @@ -0,0 +1,64 @@ +"""Generate, verify, and Modal-prep the Figment v7 delta SFT corpus.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.generate_finetune_data import V7_NAVIGATOR_COUNTS # noqa: E402 +from scripts.generate_v3_full_corpus import main as _run_full_corpus # noqa: E402 + + +DEFAULT_OUTPUT_VERSION = "figment_sft_v7_delta" +DEFAULT_TEACHER_MODEL_ID = "nvidia/nemotron-3-ultra-550b-a55b:free" +DEFAULT_NAVIGATOR_COUNT = sum(V7_NAVIGATOR_COUNTS.values()) +DEFAULT_REPAIR_COUNT = 240 +DEFAULT_ARGS = [ + "--dataset-version", + DEFAULT_OUTPUT_VERSION, + "--navigator-count", + str(DEFAULT_NAVIGATOR_COUNT), + "--repair-count", + str(DEFAULT_REPAIR_COUNT), + "--teacher-model-id", + DEFAULT_TEACHER_MODEL_ID, + "--base-start-index", + "80000", + "--shard-prefix", + "data/finetune/shards/figment_sft_v7_delta_full_shard", + "--output", + "data/finetune/figment_sft_v7_delta.jsonl", + "--case-specs", + "data/finetune/figment_sft_v7_delta_case_specs.jsonl", + "--manifest", + "data/finetune/figment_sft_v7_delta_manifest.json", + "--modal-output-dir", + "data/finetune/modal/figment_sft_v7_delta", + "--seed", + "figment-modal-sft-v7-delta", +] + + +def build_corpus_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--navigator-count", type=int, default=DEFAULT_NAVIGATOR_COUNT) + parser.add_argument("--repair-count", type=int, default=DEFAULT_REPAIR_COUNT) + parsed, remaining = parser.parse_known_args(raw_args) + defaults = list(DEFAULT_ARGS) + defaults[defaults.index("--navigator-count") + 1] = str(parsed.navigator_count) + defaults[defaults.index("--repair-count") + 1] = str(parsed.repair_count) + return defaults + remaining + + +def main(argv: list[str] | None = None) -> int: + return _run_full_corpus(build_corpus_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_v8_full_corpus.py b/scripts/generate_v8_full_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..fcbbbfb05f5478560d54f1e658fb0d0581e0a9ba --- /dev/null +++ b/scripts/generate_v8_full_corpus.py @@ -0,0 +1,66 @@ +"""Generate, verify, and Modal-prep the Figment v8 delta SFT corpus.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.generate_finetune_data import V8_NAVIGATOR_COUNTS # noqa: E402 +from scripts.generate_v3_full_corpus import main as _run_full_corpus # noqa: E402 + + +DEFAULT_OUTPUT_VERSION = "figment_sft_v8_delta" +DEFAULT_TEACHER_MODEL_ID = "nvidia/nemotron-3-ultra-550b-a55b:free" +DEFAULT_NAVIGATOR_COUNT = sum(V8_NAVIGATOR_COUNTS.values()) +DEFAULT_REPAIR_COUNT = 0 +DEFAULT_ARGS = [ + "--dataset-version", + DEFAULT_OUTPUT_VERSION, + "--navigator-count", + str(DEFAULT_NAVIGATOR_COUNT), + "--repair-count", + str(DEFAULT_REPAIR_COUNT), + "--teacher-model-id", + DEFAULT_TEACHER_MODEL_ID, + "--base-start-index", + "90000", + "--rows-per-shard", + "40", + "--shard-prefix", + "data/finetune/shards/figment_sft_v8_delta_full_shard", + "--output", + "data/finetune/figment_sft_v8_delta.jsonl", + "--case-specs", + "data/finetune/figment_sft_v8_delta_case_specs.jsonl", + "--manifest", + "data/finetune/figment_sft_v8_delta_manifest.json", + "--modal-output-dir", + "data/finetune/modal/figment_sft_v8_delta", + "--seed", + "figment-modal-sft-v8-delta", +] + + +def build_corpus_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--navigator-count", type=int, default=DEFAULT_NAVIGATOR_COUNT) + parser.add_argument("--repair-count", type=int, default=DEFAULT_REPAIR_COUNT) + parsed, remaining = parser.parse_known_args(raw_args) + defaults = list(DEFAULT_ARGS) + defaults[defaults.index("--navigator-count") + 1] = str(parsed.navigator_count) + defaults[defaults.index("--repair-count") + 1] = str(parsed.repair_count) + return defaults + remaining + + +def main(argv: list[str] | None = None) -> int: + return _run_full_corpus(build_corpus_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/generate_v9_full_corpus.py b/scripts/generate_v9_full_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..1ef2abd59ad1989f183f511ca358ec78b9663aff --- /dev/null +++ b/scripts/generate_v9_full_corpus.py @@ -0,0 +1,66 @@ +"""Generate, verify, and Modal-prep the Figment v9 delta SFT corpus.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.generate_finetune_data import V9_NAVIGATOR_COUNTS # noqa: E402 +from scripts.generate_v3_full_corpus import main as _run_full_corpus # noqa: E402 + + +DEFAULT_OUTPUT_VERSION = "figment_sft_v9_delta" +DEFAULT_TEACHER_MODEL_ID = "nvidia/nemotron-3-ultra-550b-a55b:free" +DEFAULT_NAVIGATOR_COUNT = sum(V9_NAVIGATOR_COUNTS.values()) +DEFAULT_REPAIR_COUNT = 0 +DEFAULT_ARGS = [ + "--dataset-version", + DEFAULT_OUTPUT_VERSION, + "--navigator-count", + str(DEFAULT_NAVIGATOR_COUNT), + "--repair-count", + str(DEFAULT_REPAIR_COUNT), + "--teacher-model-id", + DEFAULT_TEACHER_MODEL_ID, + "--base-start-index", + "100000", + "--rows-per-shard", + "40", + "--shard-prefix", + "data/finetune/shards/figment_sft_v9_delta_full_shard", + "--output", + "data/finetune/figment_sft_v9_delta.jsonl", + "--case-specs", + "data/finetune/figment_sft_v9_delta_case_specs.jsonl", + "--manifest", + "data/finetune/figment_sft_v9_delta_manifest.json", + "--modal-output-dir", + "data/finetune/modal/figment_sft_v9_delta", + "--seed", + "figment-modal-sft-v9-delta", +] + + +def build_corpus_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--navigator-count", type=int, default=DEFAULT_NAVIGATOR_COUNT) + parser.add_argument("--repair-count", type=int, default=DEFAULT_REPAIR_COUNT) + parsed, remaining = parser.parse_known_args(raw_args) + defaults = list(DEFAULT_ARGS) + defaults[defaults.index("--navigator-count") + 1] = str(parsed.navigator_count) + defaults[defaults.index("--repair-count") + 1] = str(parsed.repair_count) + return defaults + remaining + + +def main(argv: list[str] | None = None) -> int: + return _run_full_corpus(build_corpus_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/merge_finetune_shards.py b/scripts/merge_finetune_shards.py new file mode 100644 index 0000000000000000000000000000000000000000..56d91a07940669b341f5e25f6464ee51cdce8404 --- /dev/null +++ b/scripts/merge_finetune_shards.py @@ -0,0 +1,196 @@ +"""Merge disjoint Figment SFT teacher-generation shards.""" + +from __future__ import annotations + +import argparse +from collections import Counter +from datetime import UTC +from datetime import datetime +import hashlib +import json +from pathlib import Path +from typing import Any + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--dataset-version", required=True) + parser.add_argument("--shard-prefix", type=Path, required=True) + parser.add_argument("--shard-count", type=int, required=True) + parser.add_argument("--output", type=Path, required=True) + parser.add_argument("--case-specs", type=Path, required=True) + parser.add_argument("--manifest", type=Path, required=True) + args = parser.parse_args(argv) + + manifest = merge_shards( + dataset_version=args.dataset_version, + shard_prefix=args.shard_prefix, + shard_count=args.shard_count, + output_path=args.output, + case_specs_path=args.case_specs, + manifest_path=args.manifest, + ) + print(json.dumps(manifest, indent=2, sort_keys=True)) + return 0 + + +def merge_shards( + *, + dataset_version: str, + shard_prefix: Path, + shard_count: int, + output_path: Path, + case_specs_path: Path, + manifest_path: Path, +) -> dict[str, Any]: + if shard_count <= 0: + raise ValueError("shard_count must be positive") + + rows_by_id: dict[str, dict[str, Any]] = {} + specs_by_id: dict[str, dict[str, Any]] = {} + shard_summaries: list[dict[str, Any]] = [] + source_attempts = 0 + anti_overfit_eval_paths: set[str] = set() + anti_overfit_signature_count = 0 + anti_overfit_enabled = False + + for shard_index in range(shard_count): + dataset_shard, spec_shard, manifest_shard = shard_paths(shard_prefix, shard_index) + rows = _read_jsonl(dataset_shard) + specs = _read_jsonl(spec_shard) + source_manifest = _read_json(manifest_shard) if manifest_shard.exists() else {} + source_attempts += int(source_manifest.get("attempts") or 0) + source_exclusions = source_manifest.get("anti_overfit_exclusions") + if isinstance(source_exclusions, dict): + anti_overfit_enabled = anti_overfit_enabled or bool(source_exclusions.get("enabled")) + anti_overfit_eval_paths.update(str(path) for path in source_exclusions.get("eval_paths", []) if str(path)) + anti_overfit_signature_count = max( + anti_overfit_signature_count, + int(source_exclusions.get("signature_count") or 0), + ) + + for row in rows: + row_id = str(row.get("case_id") or row.get("uuid") or "") + if not row_id: + raise ValueError(f"{dataset_shard}: row missing case_id") + if str(row.get("version")) != dataset_version: + raise ValueError(f"{dataset_shard}: {row_id} version does not match {dataset_version}") + if row_id in rows_by_id: + raise ValueError(f"duplicate row id across shards: {row_id}") + rows_by_id[row_id] = row + + for spec in specs: + spec_id = str(spec.get("case_id") or "") + if not spec_id: + raise ValueError(f"{spec_shard}: spec missing case_id") + if str(spec.get("dataset_version") or dataset_version) != dataset_version: + raise ValueError(f"{spec_shard}: {spec_id} dataset_version does not match {dataset_version}") + if spec_id in specs_by_id: + raise ValueError(f"duplicate case spec id across shards: {spec_id}") + specs_by_id[spec_id] = spec + + shard_summaries.append( + { + "index": shard_index, + "dataset_path": str(dataset_shard), + "case_specs_path": str(spec_shard), + "manifest_path": str(manifest_shard), + "row_count": len(rows), + "case_spec_count": len(specs), + "attempts": int(source_manifest.get("attempts") or 0), + "accepted_by_failure_class": source_manifest.get("accepted_by_failure_class", {}), + "rejection_reasons": source_manifest.get("rejection_reasons", {}), + } + ) + + missing_specs = sorted(set(rows_by_id) - set(specs_by_id)) + orphan_specs = sorted(set(specs_by_id) - set(rows_by_id)) + if missing_specs: + raise ValueError(f"missing case specs for rows: {', '.join(missing_specs[:10])}") + if orphan_specs: + raise ValueError(f"case specs without rows: {', '.join(orphan_specs[:10])}") + + rows = [rows_by_id[row_id] for row_id in sorted(rows_by_id)] + specs = [specs_by_id[case_id] for case_id in sorted(specs_by_id)] + + output_path.parent.mkdir(parents=True, exist_ok=True) + case_specs_path.parent.mkdir(parents=True, exist_ok=True) + manifest_path.parent.mkdir(parents=True, exist_ok=True) + _write_jsonl(output_path, rows) + _write_jsonl(case_specs_path, specs) + + task_counts = Counter(_task_type(row) for row in rows) + category_counts = Counter(str(row.get("category") or "unknown") for row in rows) + summary = { + "dataset_version": dataset_version, + "merged_at": datetime.now(UTC).isoformat(), + "row_count": len(rows), + "case_spec_count": len(specs), + "shard_count": shard_count, + "source_attempts": source_attempts, + "output_path": str(output_path), + "case_specs_path": str(case_specs_path), + "output_sha256": _sha256_path(output_path), + "case_specs_sha256": _sha256_path(case_specs_path), + "task_type_counts": dict(sorted(task_counts.items())), + "category_counts": dict(sorted(category_counts.items())), + "anti_overfit_exclusions": { + "enabled": anti_overfit_enabled, + "eval_paths": sorted(anti_overfit_eval_paths), + "signature_count": anti_overfit_signature_count, + }, + "shards": shard_summaries, + } + manifest_path.write_text(json.dumps(summary, indent=2, sort_keys=True) + "\n", encoding="utf-8") + return summary + + +def shard_paths(shard_prefix: Path, shard_index: int) -> tuple[Path, Path, Path]: + base = f"{shard_prefix}{shard_index}" + return ( + Path(f"{base}.jsonl"), + Path(f"{base}_case_specs.jsonl"), + Path(f"{base}_manifest.json"), + ) + + +def _read_jsonl(path: Path) -> list[dict[str, Any]]: + if not path.exists(): + raise FileNotFoundError(path) + rows: list[dict[str, Any]] = [] + for line_number, line in enumerate(path.read_text(encoding="utf-8").splitlines(), start=1): + if not line.strip(): + continue + item = json.loads(line) + if not isinstance(item, dict): + raise ValueError(f"{path}:{line_number}: expected JSON object") + rows.append(item) + return rows + + +def _read_json(path: Path) -> dict[str, Any]: + item = json.loads(path.read_text(encoding="utf-8")) + if not isinstance(item, dict): + raise ValueError(f"{path}: expected JSON object") + return item + + +def _write_jsonl(path: Path, rows: list[dict[str, Any]]) -> None: + path.write_text("".join(json.dumps(row, sort_keys=True) + "\n" for row in rows), encoding="utf-8") + + +def _task_type(row: dict[str, Any]) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + return str(metadata.get("task_type") or "navigator_full") + + +def _sha256_path(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as file: + for chunk in iter(lambda: file.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/merge_v10_training_corpus.py b/scripts/merge_v10_training_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..b189d69b32b7957d5ca6efc1ae0f3b37c776b447 --- /dev/null +++ b/scripts/merge_v10_training_corpus.py @@ -0,0 +1,67 @@ +"""Merge Figment v10 delta rows with the v9 corpus and prepare Modal splits.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.merge_v8_training_corpus import main as _merge_main # noqa: E402 + + +DEFAULT_BASE = "data/finetune/figment_sft_v9.jsonl" +DEFAULT_BASE_CASE_SPECS = "data/finetune/figment_sft_v9_case_specs.jsonl" +DEFAULT_DELTA = "data/finetune/figment_sft_v10_delta.jsonl" +DEFAULT_DELTA_CASE_SPECS = "data/finetune/figment_sft_v10_delta_case_specs.jsonl" +DEFAULT_OUTPUT = "data/finetune/figment_sft_v10.jsonl" +DEFAULT_CASE_SPECS = "data/finetune/figment_sft_v10_case_specs.jsonl" +DEFAULT_MANIFEST = "data/finetune/figment_sft_v10_manifest.json" +DEFAULT_MODAL_DIR = "data/finetune/modal/figment_sft_v10" + + +def build_merge_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--base", default=DEFAULT_BASE) + parser.add_argument("--base-case-specs", default=DEFAULT_BASE_CASE_SPECS) + parser.add_argument("--delta", default=DEFAULT_DELTA) + parser.add_argument("--delta-case-specs", default=DEFAULT_DELTA_CASE_SPECS) + parser.add_argument("--output", default=DEFAULT_OUTPUT) + parser.add_argument("--case-specs", default=DEFAULT_CASE_SPECS) + parser.add_argument("--manifest", default=DEFAULT_MANIFEST) + parser.add_argument("--modal-output-dir", default=DEFAULT_MODAL_DIR) + parser.add_argument("--dataset-version", default="figment_sft_v10") + parsed, remaining = parser.parse_known_args(raw_args) + return [ + "--base", + parsed.base, + "--base-case-specs", + parsed.base_case_specs, + "--delta", + parsed.delta, + "--delta-case-specs", + parsed.delta_case_specs, + "--output", + parsed.output, + "--case-specs", + parsed.case_specs, + "--manifest", + parsed.manifest, + "--modal-output-dir", + parsed.modal_output_dir, + "--dataset-version", + parsed.dataset_version, + *remaining, + ] + + +def main(argv: list[str] | None = None) -> int: + return _merge_main(build_merge_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/merge_v11_training_corpus.py b/scripts/merge_v11_training_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..085d5dd493dd550b04eb58881303156c458a6a08 --- /dev/null +++ b/scripts/merge_v11_training_corpus.py @@ -0,0 +1,67 @@ +"""Merge Figment v11 delta rows with the v10 corpus and prepare Modal splits.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.merge_v8_training_corpus import main as _merge_main # noqa: E402 + + +DEFAULT_BASE = "data/finetune/figment_sft_v10.jsonl" +DEFAULT_BASE_CASE_SPECS = "data/finetune/figment_sft_v10_case_specs.jsonl" +DEFAULT_DELTA = "data/finetune/figment_sft_v11_delta.jsonl" +DEFAULT_DELTA_CASE_SPECS = "data/finetune/figment_sft_v11_delta_case_specs.jsonl" +DEFAULT_OUTPUT = "data/finetune/figment_sft_v11.jsonl" +DEFAULT_CASE_SPECS = "data/finetune/figment_sft_v11_case_specs.jsonl" +DEFAULT_MANIFEST = "data/finetune/figment_sft_v11_manifest.json" +DEFAULT_MODAL_DIR = "data/finetune/modal/figment_sft_v11" + + +def build_merge_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--base", default=DEFAULT_BASE) + parser.add_argument("--base-case-specs", default=DEFAULT_BASE_CASE_SPECS) + parser.add_argument("--delta", default=DEFAULT_DELTA) + parser.add_argument("--delta-case-specs", default=DEFAULT_DELTA_CASE_SPECS) + parser.add_argument("--output", default=DEFAULT_OUTPUT) + parser.add_argument("--case-specs", default=DEFAULT_CASE_SPECS) + parser.add_argument("--manifest", default=DEFAULT_MANIFEST) + parser.add_argument("--modal-output-dir", default=DEFAULT_MODAL_DIR) + parser.add_argument("--dataset-version", default="figment_sft_v11") + parsed, remaining = parser.parse_known_args(raw_args) + return [ + "--base", + parsed.base, + "--base-case-specs", + parsed.base_case_specs, + "--delta", + parsed.delta, + "--delta-case-specs", + parsed.delta_case_specs, + "--output", + parsed.output, + "--case-specs", + parsed.case_specs, + "--manifest", + parsed.manifest, + "--modal-output-dir", + parsed.modal_output_dir, + "--dataset-version", + parsed.dataset_version, + *remaining, + ] + + +def main(argv: list[str] | None = None) -> int: + return _merge_main(build_merge_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/merge_v12_training_corpus.py b/scripts/merge_v12_training_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..c84d1221adf2f8c31e1a165207000c2abff3cfb4 --- /dev/null +++ b/scripts/merge_v12_training_corpus.py @@ -0,0 +1,67 @@ +"""Merge Figment v12 delta rows with the v10 corpus and prepare Modal splits.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.merge_v8_training_corpus import main as _merge_main # noqa: E402 + + +DEFAULT_BASE = "data/finetune/figment_sft_v10.jsonl" +DEFAULT_BASE_CASE_SPECS = "data/finetune/figment_sft_v10_case_specs.jsonl" +DEFAULT_DELTA = "data/finetune/figment_sft_v12_delta.jsonl" +DEFAULT_DELTA_CASE_SPECS = "data/finetune/figment_sft_v12_delta_case_specs.jsonl" +DEFAULT_OUTPUT = "data/finetune/figment_sft_v12.jsonl" +DEFAULT_CASE_SPECS = "data/finetune/figment_sft_v12_case_specs.jsonl" +DEFAULT_MANIFEST = "data/finetune/figment_sft_v12_manifest.json" +DEFAULT_MODAL_DIR = "data/finetune/modal/figment_sft_v12" + + +def build_merge_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--base", default=DEFAULT_BASE) + parser.add_argument("--base-case-specs", default=DEFAULT_BASE_CASE_SPECS) + parser.add_argument("--delta", default=DEFAULT_DELTA) + parser.add_argument("--delta-case-specs", default=DEFAULT_DELTA_CASE_SPECS) + parser.add_argument("--output", default=DEFAULT_OUTPUT) + parser.add_argument("--case-specs", default=DEFAULT_CASE_SPECS) + parser.add_argument("--manifest", default=DEFAULT_MANIFEST) + parser.add_argument("--modal-output-dir", default=DEFAULT_MODAL_DIR) + parser.add_argument("--dataset-version", default="figment_sft_v12") + parsed, remaining = parser.parse_known_args(raw_args) + return [ + "--base", + parsed.base, + "--base-case-specs", + parsed.base_case_specs, + "--delta", + parsed.delta, + "--delta-case-specs", + parsed.delta_case_specs, + "--output", + parsed.output, + "--case-specs", + parsed.case_specs, + "--manifest", + parsed.manifest, + "--modal-output-dir", + parsed.modal_output_dir, + "--dataset-version", + parsed.dataset_version, + *remaining, + ] + + +def main(argv: list[str] | None = None) -> int: + return _merge_main(build_merge_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/merge_v13_training_corpus.py b/scripts/merge_v13_training_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..6ae7f87945f0a191cfb1c537b98438a56e959cb2 --- /dev/null +++ b/scripts/merge_v13_training_corpus.py @@ -0,0 +1,67 @@ +"""Merge Figment v13 delta rows with the v10 corpus and prepare Modal splits.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.merge_v8_training_corpus import main as _merge_main # noqa: E402 + + +DEFAULT_BASE = "data/finetune/figment_sft_v10.jsonl" +DEFAULT_BASE_CASE_SPECS = "data/finetune/figment_sft_v10_case_specs.jsonl" +DEFAULT_DELTA = "data/finetune/figment_sft_v13_delta.jsonl" +DEFAULT_DELTA_CASE_SPECS = "data/finetune/figment_sft_v13_delta_case_specs.jsonl" +DEFAULT_OUTPUT = "data/finetune/figment_sft_v13.jsonl" +DEFAULT_CASE_SPECS = "data/finetune/figment_sft_v13_case_specs.jsonl" +DEFAULT_MANIFEST = "data/finetune/figment_sft_v13_manifest.json" +DEFAULT_MODAL_DIR = "data/finetune/modal/figment_sft_v13" + + +def build_merge_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--base", default=DEFAULT_BASE) + parser.add_argument("--base-case-specs", default=DEFAULT_BASE_CASE_SPECS) + parser.add_argument("--delta", default=DEFAULT_DELTA) + parser.add_argument("--delta-case-specs", default=DEFAULT_DELTA_CASE_SPECS) + parser.add_argument("--output", default=DEFAULT_OUTPUT) + parser.add_argument("--case-specs", default=DEFAULT_CASE_SPECS) + parser.add_argument("--manifest", default=DEFAULT_MANIFEST) + parser.add_argument("--modal-output-dir", default=DEFAULT_MODAL_DIR) + parser.add_argument("--dataset-version", default="figment_sft_v13") + parsed, remaining = parser.parse_known_args(raw_args) + return [ + "--base", + parsed.base, + "--base-case-specs", + parsed.base_case_specs, + "--delta", + parsed.delta, + "--delta-case-specs", + parsed.delta_case_specs, + "--output", + parsed.output, + "--case-specs", + parsed.case_specs, + "--manifest", + parsed.manifest, + "--modal-output-dir", + parsed.modal_output_dir, + "--dataset-version", + parsed.dataset_version, + *remaining, + ] + + +def main(argv: list[str] | None = None) -> int: + return _merge_main(build_merge_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/merge_v14_training_corpus.py b/scripts/merge_v14_training_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..3ecfc42b2f14bb080abc30869b8b70fd2e76ce45 --- /dev/null +++ b/scripts/merge_v14_training_corpus.py @@ -0,0 +1,67 @@ +"""Merge Figment v14 delta rows with the v10 corpus and prepare Modal splits.""" + +from __future__ import annotations + +import argparse +from pathlib import Path +import sys + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from scripts.merge_v8_training_corpus import main as _merge_main # noqa: E402 + + +DEFAULT_BASE = "data/finetune/figment_sft_v10.jsonl" +DEFAULT_BASE_CASE_SPECS = "data/finetune/figment_sft_v10_case_specs.jsonl" +DEFAULT_DELTA = "data/finetune/figment_sft_v14_delta.jsonl" +DEFAULT_DELTA_CASE_SPECS = "data/finetune/figment_sft_v14_delta_case_specs.jsonl" +DEFAULT_OUTPUT = "data/finetune/figment_sft_v14.jsonl" +DEFAULT_CASE_SPECS = "data/finetune/figment_sft_v14_case_specs.jsonl" +DEFAULT_MANIFEST = "data/finetune/figment_sft_v14_manifest.json" +DEFAULT_MODAL_DIR = "data/finetune/modal/figment_sft_v14" + + +def build_merge_args(argv: list[str] | None = None) -> list[str]: + raw_args = list(sys.argv[1:] if argv is None else argv) + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--base", default=DEFAULT_BASE) + parser.add_argument("--base-case-specs", default=DEFAULT_BASE_CASE_SPECS) + parser.add_argument("--delta", default=DEFAULT_DELTA) + parser.add_argument("--delta-case-specs", default=DEFAULT_DELTA_CASE_SPECS) + parser.add_argument("--output", default=DEFAULT_OUTPUT) + parser.add_argument("--case-specs", default=DEFAULT_CASE_SPECS) + parser.add_argument("--manifest", default=DEFAULT_MANIFEST) + parser.add_argument("--modal-output-dir", default=DEFAULT_MODAL_DIR) + parser.add_argument("--dataset-version", default="figment_sft_v14") + parsed, remaining = parser.parse_known_args(raw_args) + return [ + "--base", + parsed.base, + "--base-case-specs", + parsed.base_case_specs, + "--delta", + parsed.delta, + "--delta-case-specs", + parsed.delta_case_specs, + "--output", + parsed.output, + "--case-specs", + parsed.case_specs, + "--manifest", + parsed.manifest, + "--modal-output-dir", + parsed.modal_output_dir, + "--dataset-version", + parsed.dataset_version, + *remaining, + ] + + +def main(argv: list[str] | None = None) -> int: + return _merge_main(build_merge_args(argv)) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/merge_v6_training_corpus.py b/scripts/merge_v6_training_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..28fa81fa17be2b6fad3ffc1b64cbb0e11c58cb7b --- /dev/null +++ b/scripts/merge_v6_training_corpus.py @@ -0,0 +1,217 @@ +"""Merge Figment v6 delta rows with audited replay rows and prepare Modal splits.""" + +from __future__ import annotations + +import argparse +from collections import Counter +from datetime import UTC +from datetime import datetime +import hashlib +import json +from pathlib import Path +import subprocess +import sys +from typing import Any + + +DEFAULT_DELTA = Path("data/finetune/figment_sft_v6_delta.jsonl") +DEFAULT_DELTA_CASE_SPECS = Path("data/finetune/figment_sft_v6_delta_case_specs.jsonl") +DEFAULT_REPLAY = Path("data/finetune/figment_sft_v6_replay.jsonl") +DEFAULT_OUTPUT = Path("data/finetune/figment_sft_v6.jsonl") +DEFAULT_CASE_SPECS = Path("data/finetune/figment_sft_v6_case_specs.jsonl") +DEFAULT_MANIFEST = Path("data/finetune/figment_sft_v6_manifest.json") +DEFAULT_MODAL_DIR = Path("data/finetune/modal/figment_sft_v6") +SOURCE_CASE_SPECS = { + "figment_sft_v3": Path("data/finetune/figment_sft_v3_case_specs.jsonl"), + "figment_sft_v4": Path("data/finetune/figment_sft_v4_case_specs.jsonl"), + "figment_sft_v5": Path("data/finetune/figment_sft_v5_case_specs.jsonl"), +} + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--delta", type=Path, default=DEFAULT_DELTA) + parser.add_argument("--delta-case-specs", type=Path, default=DEFAULT_DELTA_CASE_SPECS) + parser.add_argument("--replay", type=Path, default=DEFAULT_REPLAY) + parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT) + parser.add_argument("--case-specs", type=Path, default=DEFAULT_CASE_SPECS) + parser.add_argument("--manifest", type=Path, default=DEFAULT_MANIFEST) + parser.add_argument("--modal-output-dir", type=Path, default=DEFAULT_MODAL_DIR) + parser.add_argument("--dataset-version", default="figment_sft_v6") + parser.add_argument("--validation-fraction", type=float, default=0.1) + parser.add_argument("--seed", default="figment-modal-sft-v6") + parser.add_argument("--min-validation-group-size", type=int, default=5) + parser.add_argument("--skip-verify", action="store_true") + parser.add_argument("--skip-modal-prep", action="store_true") + args = parser.parse_args(argv) + + summary = merge_v6_corpus( + delta_path=args.delta, + delta_case_specs_path=args.delta_case_specs, + replay_path=args.replay, + output_path=args.output, + case_specs_path=args.case_specs, + manifest_path=args.manifest, + dataset_version=args.dataset_version, + ) + + verify_summary = None + if not args.skip_verify: + verify_summary = _run_json_command( + [ + sys.executable, + "scripts/verify_finetune_harness_alignment.py", + "--dataset", + str(args.output), + "--case-specs", + str(args.case_specs), + ] + ) + if verify_summary.get("passed") is not True: + raise SystemExit(f"harness verification failed: {json.dumps(verify_summary, sort_keys=True)}") + + modal_summary = None + if not args.skip_modal_prep: + modal_summary = _run_json_command( + [ + sys.executable, + "scripts/prepare_modal_finetune_dataset.py", + "--dataset", + str(args.output), + "--dataset-version", + args.dataset_version, + "--output-dir", + str(args.modal_output_dir), + "--validation-fraction", + str(args.validation_fraction), + "--seed", + args.seed, + "--min-validation-group-size", + str(args.min_validation_group_size), + ] + ) + + summary["verify"] = verify_summary + summary["modal"] = modal_summary + args.manifest.write_text(json.dumps(summary, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(summary, indent=2, sort_keys=True)) + return 0 + + +def merge_v6_corpus( + *, + delta_path: Path, + delta_case_specs_path: Path, + replay_path: Path, + output_path: Path, + case_specs_path: Path, + manifest_path: Path, + dataset_version: str, +) -> dict[str, Any]: + delta_rows = _read_jsonl(delta_path) + replay_rows = _read_jsonl(replay_path) + rows = _dedupe_rows(delta_rows + replay_rows) + specs = _case_specs_for_rows(delta_case_specs_path, rows) + + output_path.parent.mkdir(parents=True, exist_ok=True) + case_specs_path.parent.mkdir(parents=True, exist_ok=True) + manifest_path.parent.mkdir(parents=True, exist_ok=True) + _write_jsonl(output_path, rows) + _write_jsonl(case_specs_path, specs) + + return { + "dataset_version": dataset_version, + "merged_at": datetime.now(UTC).isoformat(), + "row_count": len(rows), + "delta_rows": len(delta_rows), + "replay_rows": len(replay_rows), + "case_spec_count": len(specs), + "output_path": str(output_path), + "case_specs_path": str(case_specs_path), + "output_sha256": _sha256_path(output_path), + "case_specs_sha256": _sha256_path(case_specs_path), + "task_type_counts": dict(sorted(Counter(_task_type(row) for row in rows).items())), + "category_counts": dict(sorted(Counter(str(row.get("category") or "unknown") for row in rows).items())), + "replay_source_counts": dict(sorted(Counter(_replay_source(row) for row in replay_rows).items())), + } + + +def _case_specs_for_rows(delta_case_specs_path: Path, rows: list[dict[str, Any]]) -> list[dict[str, Any]]: + specs_by_id = {str(item.get("case_id")): item for item in _read_jsonl(delta_case_specs_path)} + source_specs_cache: dict[str, dict[str, dict[str, Any]]] = {} + needed_ids = {str(row.get("metadata", {}).get("base_case_id") or row.get("case_id")) for row in rows} + for row in rows: + base_id = str(row.get("metadata", {}).get("base_case_id") or row.get("case_id")) + if base_id in specs_by_id: + continue + source_version = _source_dataset_version(row) + source_path = SOURCE_CASE_SPECS.get(source_version) + if source_path is None: + continue + if source_version not in source_specs_cache: + source_specs_cache[source_version] = { + str(item.get("case_id")): item for item in _read_jsonl(source_path) + } + source_spec = source_specs_cache[source_version].get(base_id) + if source_spec is not None: + specs_by_id[base_id] = source_spec + + missing = sorted(needed_ids - set(specs_by_id)) + if missing: + raise ValueError(f"missing case specs for rows: {', '.join(missing[:10])}") + return [specs_by_id[case_id] for case_id in sorted(needed_ids)] + + +def _dedupe_rows(rows: list[dict[str, Any]]) -> list[dict[str, Any]]: + rows_by_id: dict[str, dict[str, Any]] = {} + for row in rows: + row_id = str(row.get("case_id") or row.get("uuid") or "") + if not row_id: + raise ValueError("row missing case_id/uuid") + if row_id in rows_by_id: + raise ValueError(f"duplicate row id: {row_id}") + rows_by_id[row_id] = row + return [rows_by_id[row_id] for row_id in sorted(rows_by_id)] + + +def _source_dataset_version(row: dict[str, Any]) -> str: + replay_audit = row.get("metadata", {}).get("v6_replay_audit") + if isinstance(replay_audit, dict) and replay_audit.get("source_dataset_version"): + return str(replay_audit["source_dataset_version"]) + return str(row.get("version") or row.get("metadata", {}).get("dataset_version") or "") + + +def _replay_source(row: dict[str, Any]) -> str: + return _source_dataset_version(row) or "unknown" + + +def _task_type(row: dict[str, Any]) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + return str(metadata.get("task_type") or "navigator_full") + + +def _read_jsonl(path: Path) -> list[dict[str, Any]]: + if not path.exists(): + raise FileNotFoundError(path) + return [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()] + + +def _write_jsonl(path: Path, rows: list[dict[str, Any]]) -> None: + path.write_text("".join(json.dumps(row, sort_keys=True) + "\n" for row in rows), encoding="utf-8") + + +def _sha256_path(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as file: + for chunk in iter(lambda: file.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +def _run_json_command(cmd: list[str]) -> dict[str, Any]: + completed = subprocess.run(cmd, check=True, text=True, capture_output=True) + return json.loads(completed.stdout) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/merge_v7_training_corpus.py b/scripts/merge_v7_training_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..f9a83e4adfe5366b547804edca551e008f544a1a --- /dev/null +++ b/scripts/merge_v7_training_corpus.py @@ -0,0 +1,225 @@ +"""Merge Figment v7 delta rows with audited replay rows and prepare Modal splits.""" + +from __future__ import annotations + +import argparse +from collections import Counter +from datetime import UTC +from datetime import datetime +import hashlib +import json +from pathlib import Path +import subprocess +import sys +from typing import Any + + +DEFAULT_DELTA = Path("data/finetune/figment_sft_v7_delta.jsonl") +DEFAULT_DELTA_CASE_SPECS = Path("data/finetune/figment_sft_v7_delta_case_specs.jsonl") +DEFAULT_REPLAY = Path("data/finetune/figment_sft_v7_replay.jsonl") +DEFAULT_OUTPUT = Path("data/finetune/figment_sft_v7.jsonl") +DEFAULT_CASE_SPECS = Path("data/finetune/figment_sft_v7_case_specs.jsonl") +DEFAULT_MANIFEST = Path("data/finetune/figment_sft_v7_manifest.json") +DEFAULT_MODAL_DIR = Path("data/finetune/modal/figment_sft_v7") +SOURCE_CASE_SPECS = { + "figment_sft_v3": Path("data/finetune/figment_sft_v3_case_specs.jsonl"), + "figment_sft_v4": Path("data/finetune/figment_sft_v4_case_specs.jsonl"), + "figment_sft_v5": Path("data/finetune/figment_sft_v5_case_specs.jsonl"), + "figment_sft_v6_delta": Path("data/finetune/figment_sft_v6_delta_case_specs.jsonl"), +} + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--delta", type=Path, default=DEFAULT_DELTA) + parser.add_argument("--delta-case-specs", type=Path, default=DEFAULT_DELTA_CASE_SPECS) + parser.add_argument("--replay", type=Path, default=DEFAULT_REPLAY) + parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT) + parser.add_argument("--case-specs", type=Path, default=DEFAULT_CASE_SPECS) + parser.add_argument("--manifest", type=Path, default=DEFAULT_MANIFEST) + parser.add_argument("--modal-output-dir", type=Path, default=DEFAULT_MODAL_DIR) + parser.add_argument("--dataset-version", default="figment_sft_v7") + parser.add_argument("--validation-fraction", type=float, default=0.1) + parser.add_argument("--seed", default="figment-modal-sft-v7") + parser.add_argument("--min-validation-group-size", type=int, default=5) + parser.add_argument("--skip-verify", action="store_true") + parser.add_argument("--skip-modal-prep", action="store_true") + args = parser.parse_args(argv) + + summary = merge_v7_corpus( + delta_path=args.delta, + delta_case_specs_path=args.delta_case_specs, + replay_path=args.replay, + output_path=args.output, + case_specs_path=args.case_specs, + manifest_path=args.manifest, + dataset_version=args.dataset_version, + ) + + verify_summary = None + if not args.skip_verify: + verify_summary = _run_json_command( + [ + sys.executable, + "scripts/verify_finetune_harness_alignment.py", + "--dataset", + str(args.output), + "--case-specs", + str(args.case_specs), + ] + ) + if verify_summary.get("passed") is not True: + raise SystemExit(f"harness verification failed: {json.dumps(verify_summary, sort_keys=True)}") + + modal_summary = None + if not args.skip_modal_prep: + modal_summary = _run_json_command( + [ + sys.executable, + "scripts/prepare_modal_finetune_dataset.py", + "--dataset", + str(args.output), + "--dataset-version", + args.dataset_version, + "--output-dir", + str(args.modal_output_dir), + "--validation-fraction", + str(args.validation_fraction), + "--seed", + args.seed, + "--min-validation-group-size", + str(args.min_validation_group_size), + ] + ) + + summary["verify"] = verify_summary + summary["modal"] = modal_summary + args.manifest.write_text(json.dumps(summary, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(summary, indent=2, sort_keys=True)) + return 0 + + +def merge_v7_corpus( + *, + delta_path: Path, + delta_case_specs_path: Path, + replay_path: Path, + output_path: Path, + case_specs_path: Path, + manifest_path: Path, + dataset_version: str, +) -> dict[str, Any]: + delta_rows = _read_jsonl(delta_path) + replay_rows = _read_jsonl(replay_path) + rows = _dedupe_rows(delta_rows + replay_rows) + specs = _case_specs_for_rows(delta_case_specs_path, rows) + + output_path.parent.mkdir(parents=True, exist_ok=True) + case_specs_path.parent.mkdir(parents=True, exist_ok=True) + manifest_path.parent.mkdir(parents=True, exist_ok=True) + _write_jsonl(output_path, rows) + _write_jsonl(case_specs_path, specs) + + return { + "dataset_version": dataset_version, + "merged_at": datetime.now(UTC).isoformat(), + "row_count": len(rows), + "delta_rows": len(delta_rows), + "replay_rows": len(replay_rows), + "case_spec_count": len(specs), + "output_path": str(output_path), + "case_specs_path": str(case_specs_path), + "output_sha256": _sha256_path(output_path), + "case_specs_sha256": _sha256_path(case_specs_path), + "task_type_counts": dict(sorted(Counter(_task_type(row) for row in rows).items())), + "category_counts": dict(sorted(Counter(str(row.get("category") or "unknown") for row in rows).items())), + "replay_source_counts": dict(sorted(Counter(_replay_source(row) for row in replay_rows).items())), + } + + +def _case_specs_for_rows(delta_case_specs_path: Path, rows: list[dict[str, Any]]) -> list[dict[str, Any]]: + specs_by_id = {str(item.get("case_id")): item for item in _read_jsonl(delta_case_specs_path)} + source_specs_cache: dict[str, dict[str, dict[str, Any]]] = {} + needed_ids = {str(row.get("metadata", {}).get("base_case_id") or row.get("case_id")) for row in rows} + for row in rows: + base_id = str(row.get("metadata", {}).get("base_case_id") or row.get("case_id")) + if base_id in specs_by_id: + continue + source_version = _source_dataset_version(row) + source_path = SOURCE_CASE_SPECS.get(source_version) + if source_path is None: + continue + if source_version not in source_specs_cache: + source_specs_cache[source_version] = { + str(item.get("case_id")): item for item in _read_jsonl(source_path) + } + source_spec = source_specs_cache[source_version].get(base_id) + if source_spec is not None: + specs_by_id[base_id] = source_spec + + missing = sorted(needed_ids - set(specs_by_id)) + if missing: + raise ValueError(f"missing case specs for rows: {', '.join(missing[:10])}") + return [specs_by_id[case_id] for case_id in sorted(needed_ids)] + + +def _dedupe_rows(rows: list[dict[str, Any]]) -> list[dict[str, Any]]: + rows_by_id: dict[str, dict[str, Any]] = {} + for row in rows: + row_id = str(row.get("case_id") or row.get("uuid") or "") + if not row_id: + raise ValueError("row missing case_id/uuid") + if row_id in rows_by_id: + raise ValueError(f"duplicate row id: {row_id}") + rows_by_id[row_id] = row + return [rows_by_id[row_id] for row_id in sorted(rows_by_id)] + + +def _source_dataset_version(row: dict[str, Any]) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + v7_audit = metadata.get("v7_replay_audit") + if isinstance(v7_audit, dict): + if v7_audit.get("original_source_dataset_version"): + return str(v7_audit["original_source_dataset_version"]) + if v7_audit.get("source_bucket") == "figment_sft_v6_delta": + return "figment_sft_v6_delta" + v6_audit = metadata.get("v6_replay_audit") + if isinstance(v6_audit, dict) and v6_audit.get("source_dataset_version"): + return str(v6_audit["source_dataset_version"]) + return str(row.get("version") or metadata.get("dataset_version") or "") + + +def _replay_source(row: dict[str, Any]) -> str: + return _source_dataset_version(row) or "unknown" + + +def _task_type(row: dict[str, Any]) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + return str(metadata.get("task_type") or "navigator_full") + + +def _read_jsonl(path: Path) -> list[dict[str, Any]]: + if not path.exists(): + raise FileNotFoundError(path) + return [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()] + + +def _write_jsonl(path: Path, rows: list[dict[str, Any]]) -> None: + path.write_text("".join(json.dumps(row, sort_keys=True) + "\n" for row in rows), encoding="utf-8") + + +def _sha256_path(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as file: + for chunk in iter(lambda: file.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +def _run_json_command(cmd: list[str]) -> dict[str, Any]: + completed = subprocess.run(cmd, check=True, text=True, capture_output=True) + return json.loads(completed.stdout) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/merge_v8_training_corpus.py b/scripts/merge_v8_training_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..47540131998b2bd46af923c03fb281da7e06badf --- /dev/null +++ b/scripts/merge_v8_training_corpus.py @@ -0,0 +1,422 @@ +"""Merge Figment v8 delta rows with the v7 corpus and prepare Modal splits.""" + +from __future__ import annotations + +import argparse +from collections import Counter +from datetime import UTC +from datetime import datetime +import hashlib +import json +from pathlib import Path +import subprocess +import sys +from typing import Any + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from figment.focused_repair import build_focused_repair_prompts # noqa: E402 +from figment.eval_metrics import bucket_expected_observation_cues # noqa: E402 +from figment.observation_targets import required_observation_targets # noqa: E402 +from figment.prompt_builder import build_prompt # noqa: E402 +from figment.retrieval import known_card_ids # noqa: E402 +from figment.retrieval import load_protocol_cards # noqa: E402 +from figment.retrieval import query_from_intake # noqa: E402 +from figment.retrieval import search_protocol_cards # noqa: E402 +from figment.rules import run_red_flag_checks # noqa: E402 +from figment.trace import stable_hash # noqa: E402 +from figment.validators import urgency_floor_from_rules # noqa: E402 +from figment.validators import validate_navigator_output # noqa: E402 +from scripts.augment_finetune_repair_rows import _corrupt_output # noqa: E402 +from scripts.augment_finetune_repair_rows import _extra_failures_for_scope # noqa: E402 +from scripts.generate_finetune_data import _required_retrieved_ids # noqa: E402 +from scripts.generate_finetune_data import _expected_candidate_cards # noqa: E402 +from scripts.generate_finetune_data import _expected_missing_observations # noqa: E402 +from scripts.generate_finetune_data import _expected_source_cards # noqa: E402 +from scripts.generate_finetune_data import ensure_retrieved_cards # noqa: E402 +from scripts.generate_finetune_data import uses_v7_source_card_policy # noqa: E402 + + +DEFAULT_BASE = Path("data/finetune/figment_sft_v7.jsonl") +DEFAULT_BASE_CASE_SPECS = Path("data/finetune/figment_sft_v7_case_specs.jsonl") +DEFAULT_DELTA = Path("data/finetune/figment_sft_v8_delta.jsonl") +DEFAULT_DELTA_CASE_SPECS = Path("data/finetune/figment_sft_v8_delta_case_specs.jsonl") +DEFAULT_OUTPUT = Path("data/finetune/figment_sft_v8.jsonl") +DEFAULT_CASE_SPECS = Path("data/finetune/figment_sft_v8_case_specs.jsonl") +DEFAULT_MANIFEST = Path("data/finetune/figment_sft_v8_manifest.json") +DEFAULT_MODAL_DIR = Path("data/finetune/modal/figment_sft_v8") + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--base", type=Path, default=DEFAULT_BASE) + parser.add_argument("--base-case-specs", type=Path, default=DEFAULT_BASE_CASE_SPECS) + parser.add_argument("--delta", type=Path, default=DEFAULT_DELTA) + parser.add_argument("--delta-case-specs", type=Path, default=DEFAULT_DELTA_CASE_SPECS) + parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT) + parser.add_argument("--case-specs", type=Path, default=DEFAULT_CASE_SPECS) + parser.add_argument("--manifest", type=Path, default=DEFAULT_MANIFEST) + parser.add_argument("--modal-output-dir", type=Path, default=DEFAULT_MODAL_DIR) + parser.add_argument("--dataset-version", default="figment_sft_v8") + parser.add_argument("--validation-fraction", type=float, default=0.1) + parser.add_argument("--seed", default="figment-modal-sft-v8") + parser.add_argument("--min-validation-group-size", type=int, default=5) + parser.add_argument("--skip-verify", action="store_true") + parser.add_argument("--skip-modal-prep", action="store_true") + args = parser.parse_args(argv) + + summary = merge_v8_corpus( + base_path=args.base, + base_case_specs_path=args.base_case_specs, + delta_path=args.delta, + delta_case_specs_path=args.delta_case_specs, + output_path=args.output, + case_specs_path=args.case_specs, + dataset_version=args.dataset_version, + ) + + verify_summary = None + if not args.skip_verify: + verify_summary = _run_json_command( + [ + sys.executable, + "scripts/verify_finetune_harness_alignment.py", + "--dataset", + str(args.output), + "--case-specs", + str(args.case_specs), + ] + ) + if verify_summary.get("passed") is not True: + raise SystemExit(f"harness verification failed: {json.dumps(verify_summary, sort_keys=True)}") + + modal_summary = None + if not args.skip_modal_prep: + modal_summary = _run_json_command( + [ + sys.executable, + "scripts/prepare_modal_finetune_dataset.py", + "--dataset", + str(args.output), + "--dataset-version", + args.dataset_version, + "--output-dir", + str(args.modal_output_dir), + "--validation-fraction", + str(args.validation_fraction), + "--seed", + args.seed, + "--min-validation-group-size", + str(args.min_validation_group_size), + ] + ) + + summary["verify"] = verify_summary + summary["modal"] = modal_summary + args.manifest.parent.mkdir(parents=True, exist_ok=True) + args.manifest.write_text(json.dumps(summary, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(summary, indent=2, sort_keys=True)) + return 0 + + +def merge_v8_corpus( + *, + base_path: Path, + base_case_specs_path: Path, + delta_path: Path, + delta_case_specs_path: Path, + output_path: Path, + case_specs_path: Path, + dataset_version: str, +) -> dict[str, Any]: + base_rows = _read_jsonl(base_path) + delta_rows = _read_jsonl(delta_path) + rows = _dedupe_rows(base_rows + delta_rows) + specs = _case_specs_for_rows( + rows, + source_case_specs=[base_case_specs_path, delta_case_specs_path], + ) + spec_refresh_summary = _refresh_case_specs_for_current_harness(specs) + refresh_summary = _refresh_prompts_for_current_harness(rows, specs) + + output_path.parent.mkdir(parents=True, exist_ok=True) + case_specs_path.parent.mkdir(parents=True, exist_ok=True) + _write_jsonl(output_path, rows) + _write_jsonl(case_specs_path, specs) + + return { + "dataset_version": dataset_version, + "merged_at": datetime.now(UTC).isoformat(), + "row_count": len(rows), + "base_rows": len(base_rows), + "delta_rows": len(delta_rows), + "case_spec_count": len(specs), + "output_path": str(output_path), + "case_specs_path": str(case_specs_path), + "output_sha256": _sha256_path(output_path), + "case_specs_sha256": _sha256_path(case_specs_path), + "task_type_counts": dict(sorted(Counter(_task_type(row) for row in rows).items())), + "category_counts": dict(sorted(Counter(str(row.get("category") or "unknown") for row in rows).items())), + "case_spec_refresh": spec_refresh_summary, + "prompt_refresh": refresh_summary, + } + + +def _refresh_case_specs_for_current_harness(specs: list[dict[str, Any]]) -> dict[str, Any]: + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + changed: Counter[str] = Counter() + changed_specs = 0 + for spec in specs: + spec_changed = False + harness = _harness_for_spec(spec, {"version": spec.get("dataset_version")}, cards_by_id) + synthetic_spec = _synthetic_spec_for_case_spec(spec) + expected_source = _expected_source_cards( + synthetic_spec, + harness["rule_results"], + harness["retrieved_ids"], + ) + expected_candidates = _expected_candidate_cards(synthetic_spec, harness["rule_results"]) + expected_missing = _expected_missing_observations( + synthetic_spec, + [card_id for card_id in expected_source if card_id in harness["retrieved_ids"]], + cards_by_id, + ) + updates = { + "expected_red_flag_rule_ids": [str(rule["rule_id"]) for rule in harness["rule_results"]], + "expected_min_protocol_urgency": harness["urgency_floor"], + "expected_source_card_ids": expected_source, + "expected_candidate_pathway_card_ids": expected_candidates, + "expected_missing_observations": expected_missing, + "retrieved_card_ids": harness["retrieved_ids"], + } + cue_buckets = bucket_expected_observation_cues(expected_missing) + updates.update( + { + "expected_model_observation_cues": cue_buckets["model"], + "expected_handoff_cues": cue_buckets["handoff"], + "expected_harness_evidence_cues": cue_buckets["harness"], + } + ) + for key, value in updates.items(): + if spec.get(key) != value: + changed[key] += 1 + spec[key] = value + spec_changed = True + if spec_changed: + changed_specs += 1 + return { + "policy_version": 1, + "updated_field_counts": dict(sorted(changed.items())), + "updated_specs": changed_specs, + } + + +def _synthetic_spec_for_case_spec(spec: dict[str, Any]) -> Any: + return type( + "SyntheticSpecForV8MergeCaseSpecRefresh", + (), + { + "target_protocol_card_id": str(spec.get("target_protocol_card_id") or ""), + "dataset_version": str(spec.get("dataset_version") or ""), + "failure_class": str(spec.get("failure_class") or ""), + }, + )() + + +def _refresh_prompts_for_current_harness(rows: list[dict[str, Any]], specs: list[dict[str, Any]]) -> dict[str, Any]: + specs_by_id = {str(spec.get("case_id") or ""): spec for spec in specs} + rows_by_id = {str(row.get("case_id") or row.get("uuid") or ""): row for row in rows} + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + refreshed: Counter[str] = Counter() + skipped: Counter[str] = Counter() + + for row in rows: + row_id = str(row.get("case_id") or row.get("uuid") or "") + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + base_case_id = str(metadata.get("base_case_id") or row_id) + spec = specs_by_id.get(base_case_id) + messages = row.get("messages") + if spec is None or not isinstance(messages, list) or len(messages) < 2: + skipped["missing_spec_or_messages"] += 1 + continue + + harness = _harness_for_spec(spec, row, cards_by_id) + task_type = str(metadata.get("task_type") or "navigator_full") + if task_type == "focused_repair": + prompt = _focused_repair_prompt_for_row( + row=row, + rows_by_id=rows_by_id, + spec=spec, + harness=harness, + ) + if prompt is None: + skipped["focused_repair_prompt_not_refreshed"] += 1 + continue + prompt_text = prompt + else: + prompt_text = harness["prompt"] + + if not isinstance(row.get("metadata"), dict): + row["metadata"] = metadata + if not isinstance(messages[0], dict): + skipped["bad_user_message_shape"] += 1 + continue + messages[0]["content"] = prompt_text + metadata["prompt_hash"] = stable_hash(prompt_text) + metadata["prompt_template_hash"] = harness["prompt_template_hash"] + refreshed[task_type] += 1 + + return { + "refreshed_rows": sum(refreshed.values()), + "refreshed_by_task_type": dict(sorted(refreshed.items())), + "skipped": dict(sorted(skipped.items())), + "policy_version": 1, + } + + +def _harness_for_spec(spec: dict[str, Any], row: dict[str, Any], cards_by_id: dict[str, dict[str, Any]]) -> dict[str, Any]: + intake = spec["structured_intake"] + rule_results = [rule.to_dict() for rule in run_red_flag_checks(intake)] + floor = urgency_floor_from_rules(rule_results) + retrieved = search_protocol_cards(query_from_intake(intake), limit=6) + spec_dataset_version = str(spec.get("dataset_version") or row.get("version") or "") + if uses_v7_source_card_policy(spec_dataset_version): + synthetic_spec = type( + "SyntheticSpecForV8MergeRefresh", + (), + { + "target_protocol_card_id": str(spec.get("target_protocol_card_id") or ""), + "dataset_version": spec_dataset_version, + }, + )() + retrieved = ensure_retrieved_cards( + retrieved, + required_ids=_required_retrieved_ids(synthetic_spec, rule_results), + cards_by_id=cards_by_id, + limit=6, + ) + prompt, prompt_template_hash = build_prompt(intake, retrieved, rule_results, floor) + return { + "prompt": prompt, + "prompt_template_hash": prompt_template_hash, + "rule_results": rule_results, + "urgency_floor": floor, + "retrieved": retrieved, + "retrieved_ids": [str(item.get("card_id", "")) for item in retrieved if item.get("card_id")], + } + + +def _focused_repair_prompt_for_row( + *, + row: dict[str, Any], + rows_by_id: dict[str, dict[str, Any]], + spec: dict[str, Any], + harness: dict[str, Any], +) -> str | None: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + base_case_id = str(metadata.get("base_case_id") or "") + base_row = rows_by_id.get(base_case_id) + if base_row is None: + return None + repair_scope = str(metadata.get("repair_scope") or "") + if not repair_scope: + return None + try: + base_gold = json.loads(base_row["messages"][1]["content"]) + except (KeyError, TypeError, json.JSONDecodeError): + return None + previous_output = _corrupt_output(base_gold, repair_scope, str(harness["urgency_floor"])) + if previous_output is None: + return None + validation = validate_navigator_output( + previous_output, + known_card_ids=known_card_ids(), + urgency_floor=str(harness["urgency_floor"]), + confirmed_intake=spec["structured_intake"], + rule_results=harness["rule_results"], + retrieved_card_ids=set(harness["retrieved_ids"]), + retrieved_cards=harness["retrieved"], + strict_schema=True, + ).to_dict() + focused_prompt = next( + ( + item + for item in build_focused_repair_prompts( + original_prompt=str(harness["prompt"]), + previous_output=previous_output, + failures=list(validation.get("failures", [])) + + _extra_failures_for_scope(previous_output, spec, repair_scope), + urgency_floor=str(harness["urgency_floor"]), + required_observation_targets=required_observation_targets(harness["retrieved"]), + ) + if item.scope.name == repair_scope + ), + None, + ) + return focused_prompt.prompt if focused_prompt is not None else None + + +def _case_specs_for_rows(rows: list[dict[str, Any]], *, source_case_specs: list[Path]) -> list[dict[str, Any]]: + specs_by_id: dict[str, dict[str, Any]] = {} + for path in source_case_specs: + for spec in _read_jsonl(path): + case_id = str(spec.get("case_id") or "") + if case_id: + specs_by_id[case_id] = spec + + needed_ids = {_row_case_id(row) for row in rows} + missing = sorted(needed_ids - set(specs_by_id)) + if missing: + raise ValueError(f"missing case specs for rows: {', '.join(missing[:10])}") + return [specs_by_id[case_id] for case_id in sorted(needed_ids)] + + +def _row_case_id(row: dict[str, Any]) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + return str(metadata.get("base_case_id") or row.get("case_id") or row.get("uuid") or "") + + +def _dedupe_rows(rows: list[dict[str, Any]]) -> list[dict[str, Any]]: + rows_by_id: dict[str, dict[str, Any]] = {} + for row in rows: + row_id = str(row.get("case_id") or row.get("uuid") or "") + if not row_id: + raise ValueError("row missing case_id/uuid") + if row_id in rows_by_id: + raise ValueError(f"duplicate row id: {row_id}") + rows_by_id[row_id] = row + return [rows_by_id[row_id] for row_id in sorted(rows_by_id)] + + +def _task_type(row: dict[str, Any]) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + return str(metadata.get("task_type") or "navigator_full") + + +def _read_jsonl(path: Path) -> list[dict[str, Any]]: + if not path.exists(): + raise FileNotFoundError(path) + return [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()] + + +def _write_jsonl(path: Path, rows: list[dict[str, Any]]) -> None: + path.write_text("".join(json.dumps(row, sort_keys=True) + "\n" for row in rows), encoding="utf-8") + + +def _sha256_path(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as file: + for chunk in iter(lambda: file.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +def _run_json_command(cmd: list[str]) -> dict[str, Any]: + completed = subprocess.run(cmd, check=True, text=True, capture_output=True) + return json.loads(completed.stdout) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/prepare_modal_finetune_dataset.py b/scripts/prepare_modal_finetune_dataset.py new file mode 100644 index 0000000000000000000000000000000000000000..4fe914e2afbe410fdb60676fc979cb722c037937 --- /dev/null +++ b/scripts/prepare_modal_finetune_dataset.py @@ -0,0 +1,204 @@ +"""Prepare Figment SFT JSONL for Modal fine-tuning. + +The generated SFT rows are already harness-aligned. This script keeps that +shape intact, validates the two-message chat contract, and writes a small +train/validation split that a Modal job can stage into a Volume. +""" + +from __future__ import annotations + +import argparse +from collections import Counter +from collections import defaultdict +from datetime import UTC +from datetime import datetime +import hashlib +import json +from pathlib import Path +from typing import Any + + +DEFAULT_DATASET_VERSION = "figment_sft_v1" +DEFAULT_DATASET = Path("data/finetune/figment_sft_v1.jsonl") +DEFAULT_OUTPUT_ROOT = Path("data/finetune/modal") + + +class DatasetPrepError(ValueError): + """Raised when an SFT row is not safe to hand to the Modal trainer.""" + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--dataset", type=Path, default=DEFAULT_DATASET) + parser.add_argument("--dataset-version", default=DEFAULT_DATASET_VERSION) + parser.add_argument("--output-dir", type=Path, default=None) + parser.add_argument("--validation-fraction", type=float, default=0.1) + parser.add_argument("--seed", default="figment-modal-sft-v1") + parser.add_argument("--min-validation-group-size", type=int, default=5) + args = parser.parse_args(argv) + + output_dir = args.output_dir or DEFAULT_OUTPUT_ROOT / args.dataset_version + manifest = prepare_dataset( + dataset_path=args.dataset, + output_dir=output_dir, + dataset_version=args.dataset_version, + validation_fraction=args.validation_fraction, + seed=args.seed, + min_validation_group_size=args.min_validation_group_size, + ) + print(json.dumps(manifest, indent=2, sort_keys=True)) + return 0 + + +def prepare_dataset( + *, + dataset_path: Path, + output_dir: Path, + dataset_version: str, + validation_fraction: float = 0.1, + seed: str = "figment-modal-sft-v1", + min_validation_group_size: int = 5, +) -> dict[str, Any]: + if not dataset_path.exists(): + raise DatasetPrepError(f"dataset does not exist: {dataset_path}") + if not 0 <= validation_fraction < 1: + raise DatasetPrepError("--validation-fraction must be in [0, 1)") + if min_validation_group_size < 2: + raise DatasetPrepError("--min-validation-group-size must be at least 2") + + rows = _read_jsonl(dataset_path) + if not rows: + raise DatasetPrepError(f"dataset is empty: {dataset_path}") + + seen_ids: set[str] = set() + for row_number, row in enumerate(rows, start=1): + _validate_row(row, row_number) + row_id = _row_id(row) + if row_id in seen_ids: + raise DatasetPrepError(f"row {row_number}: duplicate row id {row_id!r}") + seen_ids.add(row_id) + + train_rows, validation_rows = _split_rows( + rows, + validation_fraction=validation_fraction, + seed=seed, + min_validation_group_size=min_validation_group_size, + ) + + output_dir.mkdir(parents=True, exist_ok=True) + train_path = output_dir / "train.jsonl" + validation_path = output_dir / "validation.jsonl" + manifest_path = output_dir / "manifest.json" + _write_jsonl(train_path, train_rows) + _write_jsonl(validation_path, validation_rows) + + manifest = { + "dataset_version": dataset_version, + "generated_at": datetime.now(UTC).isoformat(), + "source_dataset": str(dataset_path), + "row_count": len(rows), + "train_count": len(train_rows), + "validation_count": len(validation_rows), + "task_type_counts": dict(sorted(Counter(_task_type(row) for row in rows).items())), + "group_counts": dict(sorted(Counter(_group_key(row) for row in rows).items())), + "train_group_counts": dict(sorted(Counter(_group_key(row) for row in train_rows).items())), + "validation_group_counts": dict(sorted(Counter(_group_key(row) for row in validation_rows).items())), + "validation_fraction": validation_fraction, + "seed": seed, + "min_validation_group_size": min_validation_group_size, + "train_path": str(train_path), + "validation_path": str(validation_path), + "train_sha256": _sha256_path(train_path), + "validation_sha256": _sha256_path(validation_path), + } + manifest_path.write_text(json.dumps(manifest, indent=2, sort_keys=True) + "\n", encoding="utf-8") + return manifest + + +def _read_jsonl(path: Path) -> list[dict[str, Any]]: + rows: list[dict[str, Any]] = [] + for line_number, line in enumerate(path.read_text(encoding="utf-8").splitlines(), start=1): + if not line.strip(): + continue + try: + item = json.loads(line) + except json.JSONDecodeError as exc: + raise DatasetPrepError(f"{path}:{line_number}: invalid JSON: {exc}") from exc + if not isinstance(item, dict): + raise DatasetPrepError(f"{path}:{line_number}: expected object row") + rows.append(item) + return rows + + +def _write_jsonl(path: Path, rows: list[dict[str, Any]]) -> None: + path.write_text("".join(json.dumps(row, sort_keys=True) + "\n" for row in rows), encoding="utf-8") + + +def _validate_row(row: dict[str, Any], row_number: int) -> None: + messages = row.get("messages") + if not isinstance(messages, list) or [message.get("role") for message in messages] != ["user", "assistant"]: + raise DatasetPrepError(f"row {row_number}: expected user/assistant messages") + for message_index, message in enumerate(messages, start=1): + content = message.get("content") + if not isinstance(content, str) or not content.strip(): + raise DatasetPrepError(f"row {row_number}: message {message_index} has empty content") + if not _row_id(row): + raise DatasetPrepError(f"row {row_number}: missing uuid or case_id") + + +def _split_rows( + rows: list[dict[str, Any]], + *, + validation_fraction: float, + seed: str, + min_validation_group_size: int, +) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]: + groups: dict[str, list[dict[str, Any]]] = defaultdict(list) + for row in rows: + groups[_group_key(row)].append(row) + + validation_ids: set[str] = set() + for group_rows in groups.values(): + if validation_fraction == 0 or len(group_rows) < min_validation_group_size: + continue + validation_count = max(1, round(len(group_rows) * validation_fraction)) + validation_count = min(validation_count, len(group_rows) - 1) + ranked = sorted(group_rows, key=lambda row: _split_key(row, seed)) + validation_ids.update(_row_id(row) for row in ranked[:validation_count]) + + train_rows = [row for row in rows if _row_id(row) not in validation_ids] + validation_rows = [row for row in rows if _row_id(row) in validation_ids] + return train_rows, validation_rows + + +def _split_key(row: dict[str, Any], seed: str) -> str: + return hashlib.sha256(f"{seed}:{_row_id(row)}".encode("utf-8")).hexdigest() + + +def _row_id(row: dict[str, Any]) -> str: + return str(row.get("uuid") or row.get("case_id") or "") + + +def _group_key(row: dict[str, Any]) -> str: + task_type = _task_type(row) + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + if task_type == "focused_repair": + return f"focused_repair:{metadata.get('repair_scope') or row.get('category') or 'unknown'}" + return f"{task_type}:{row.get('category') or 'unknown'}" + + +def _task_type(row: dict[str, Any]) -> str: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + return str(metadata.get("task_type") or "navigator_full") + + +def _sha256_path(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as file: + for chunk in iter(lambda: file.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/run_local_4b_evidence.py b/scripts/run_local_4b_evidence.py new file mode 100644 index 0000000000000000000000000000000000000000..c7769eb53b77d704dcc23bee75e1b8d1f419c3aa --- /dev/null +++ b/scripts/run_local_4b_evidence.py @@ -0,0 +1,463 @@ +#!/usr/bin/env python3 +"""Capture evidence for the full-weight local 4B route.""" + +from __future__ import annotations + +import argparse +from contextlib import contextmanager +import hashlib +import ipaddress +import json +import os +from pathlib import Path +import sys +from time import gmtime, strftime +from typing import Any +import urllib.error +import urllib.parse +import urllib.request + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from figment.config import FigmentConfig, NVIDIA_NEMOTRON_3_NANO_4B_BF16_MODEL_ID # noqa: E402 +from figment.trace import stable_hash # noqa: E402 +from scripts.run_eval import run_eval # noqa: E402 +from scripts.smoke_model_route import run_smoke # noqa: E402 + + +DEFAULT_CASE_PATHS = ( + Path("data/eval/initial_handwritten_cases.jsonl"), + Path("data/eval/adversarial_strict_cases.jsonl"), + Path("data/eval/comprehensive_hosted_cases.jsonl"), +) +DEFAULT_BASE_URL = "http://127.0.0.1:8001/v1" +DEFAULT_TIMEOUT_SECONDS = 45.0 +FULL_WEIGHT_MODEL_REPO = "nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16" +FULL_WEIGHT_REVISION = "dfaf35de3e30f1867dd8dbc38a7fc9fb52d3914f" +FULL_WEIGHT_SHA256 = "55d4e2519456c4a9bddf596b0748d630e3b2ce6ff6f4c2b7ed3e07e2b00dad42" +FULL_WEIGHT_BYTES = 7_947_142_640 + + +def run_evidence( + *, + base_url: str, + model_id: str, + output_dir: Path, + case_paths: list[Path], + limit: int | None, + timeout_seconds: float, + smoke_only: bool = False, + force_eval: bool = False, +) -> dict[str, Any]: + normalized_base_url = _normalize_base_url(base_url) + output_dir.mkdir(parents=True, exist_ok=True) + + endpoint_metadata = _probe_models_endpoint(normalized_base_url, timeout_seconds) + _write_json(output_dir / "endpoint_metadata.json", endpoint_metadata) + + summary: dict[str, Any] = { + "status": "endpoint_unavailable" if endpoint_metadata["status"] != "passed" else "endpoint_available", + "output_dir": str(output_dir), + "base_url": normalized_base_url, + "model_id": model_id, + "full_weight_artifact": { + "repo": FULL_WEIGHT_MODEL_REPO, + "revision": FULL_WEIGHT_REVISION, + "model_safetensors_bytes": FULL_WEIGHT_BYTES, + "model_safetensors_sha256": FULL_WEIGHT_SHA256, + }, + "endpoint_metadata_path": str(output_dir / "endpoint_metadata.json"), + "route_smoke_path": None, + "eval_records_path": None, + "eval_summary_path": None, + "counts_as_no_cloud_route_proof": False, + "counts_as_50_case_local_llm_competence": False, + } + if endpoint_metadata["status"] != "passed": + _write_json(output_dir / "summary.json", summary) + return summary + + with _local_4b_env(normalized_base_url, model_id, timeout_seconds): + smoke = run_smoke() + smoke_path = output_dir / "route_smoke.json" + _write_json(smoke_path, smoke) + summary["route_smoke_path"] = str(smoke_path) + summary["route_smoke_status"] = smoke.get("status") + summary["counts_as_no_cloud_route_proof"] = bool( + (smoke.get("local_llm_evidence") or {}).get("counts_as_no_cloud_route_proof") + ) + + if smoke_only: + summary["status"] = "smoke_passed" if smoke.get("status") == "passed" else "smoke_failed" + _write_json(output_dir / "summary.json", summary) + return summary + + if smoke.get("status") != "passed" and not force_eval: + summary["status"] = "smoke_failed_eval_skipped" + summary["eval_skip_reason"] = "route smoke did not prove configured-model validation" + _write_json(output_dir / "summary.json", summary) + return summary + + eval_records_path = output_dir / "local_4b_eval.jsonl" + config = FigmentConfig( + figment_mode="local", + model_stack="local_4b_parakeet", + model_backend="llama_cpp", + audio_backend="none", + local_model_id=model_id, + llama_base_url=normalized_base_url, + ).validated() + eval_summary = run_eval( + case_paths=case_paths, + output_path=eval_records_path, + config=config, + limit=limit, + ) + eval_summary_path = output_dir / "eval_summary.json" + _write_json(eval_summary_path, eval_summary) + eval_manifest = _build_eval_evidence_manifest( + eval_records_path=eval_records_path, + eval_summary=eval_summary, + endpoint_metadata=endpoint_metadata, + route_smoke=smoke, + config=config, + ) + eval_manifest_path = output_dir / "eval_evidence_manifest.json" + _write_json(eval_manifest_path, eval_manifest) + + local_evidence = eval_summary.get("local_llm_evidence") or {} + summary.update( + { + "status": "eval_completed", + "eval_records_path": str(eval_records_path), + "eval_summary_path": str(eval_summary_path), + "eval_evidence_manifest_path": str(eval_manifest_path), + "total_cases": eval_summary.get("total_cases"), + "competence_successes": eval_summary.get("competence_successes"), + "fallback_uses": eval_summary.get("fallback_uses"), + "final_validation_successes": eval_summary.get("final_validation_successes"), + "latency_ms": eval_manifest.get("latency_ms"), + "trace_hash_count": eval_manifest.get("trace_hash_count"), + "missing_trace_hash_case_ids": eval_manifest.get("missing_trace_hash_case_ids"), + "counts_as_50_case_local_llm_competence": bool( + local_evidence.get("counts_as_50_case_local_llm_competence") + ), + } + ) + _write_json(output_dir / "summary.json", summary) + return summary + + +def _probe_models_endpoint(base_url: str, timeout_seconds: float) -> dict[str, Any]: + models_url = _models_url(base_url) + request = urllib.request.Request(models_url, method="GET") + try: + with urllib.request.urlopen(request, timeout=timeout_seconds) as response: + payload = json.loads(response.read().decode("utf-8")) + except (OSError, TimeoutError, urllib.error.URLError, json.JSONDecodeError) as exc: + return { + "status": "failed", + "models_url": models_url, + "error": str(exc), + } + return { + "status": "passed", + "models_url": models_url, + "payload": payload, + } + + +def _normalize_base_url(base_url: str) -> str: + stripped = base_url.strip().rstrip("/") + if not stripped: + return DEFAULT_BASE_URL + parts = urllib.parse.urlsplit(stripped) + path = parts.path.rstrip("/") + for suffix in ("/chat/completions", "/models"): + if path.endswith(suffix): + path = path[: -len(suffix)] or "/" + return urllib.parse.urlunsplit((parts.scheme, parts.netloc, path.rstrip("/"), "", "")) + + +def _models_url(base_url: str) -> str: + return f"{base_url.rstrip('/')}/models" + + +def _build_eval_evidence_manifest( + *, + eval_records_path: Path, + eval_summary: dict[str, Any], + endpoint_metadata: dict[str, Any], + route_smoke: dict[str, Any], + config: FigmentConfig, +) -> dict[str, Any]: + records = _read_eval_records(eval_records_path) + endpoint_payload = endpoint_metadata.get("payload") if isinstance(endpoint_metadata.get("payload"), dict) else {} + smoke_evidence = route_smoke.get("local_llm_evidence") if isinstance(route_smoke.get("local_llm_evidence"), dict) else {} + local_evidence = ( + eval_summary.get("local_llm_evidence") + if isinstance(eval_summary.get("local_llm_evidence"), dict) + else {} + ) + latency_values = [ + float(record["latency_ms"]) + for record in records + if isinstance(record.get("latency_ms"), int | float) + ] + trace_entries = [ + {"case_id": record.get("case_id"), "trace_hash": record.get("trace_hash")} + for record in records + if record.get("trace_hash") + ] + missing_trace_hash_case_ids = [ + str(record.get("case_id")) + for record in records + if not record.get("trace_hash") + ] + return { + "evidence_version": 1, + "manifest_hash_inputs": { + "eval_records_sha256": _file_sha256(eval_records_path), + "endpoint_payload_hash": stable_hash(endpoint_payload), + "route_smoke_hash": stable_hash(route_smoke), + }, + "model_server_metadata": { + "base_url": config.llama_base_url, + "models_url": endpoint_metadata.get("models_url"), + "models_status": endpoint_metadata.get("status"), + "advertised_model_ids": _advertised_model_ids(endpoint_payload), + "models_payload_hash": stable_hash(endpoint_payload), + }, + "configured_route": { + "figment_mode": config.figment_mode, + "model_stack": config.model_stack, + "model_backend": config.model_backend, + "audio_backend": config.audio_backend, + "active_model_id": config.active_model_id, + "local_model_id": config.local_model_id, + "llama_base_url": config.llama_base_url, + "full_weight_artifact": { + "repo": FULL_WEIGHT_MODEL_REPO, + "revision": FULL_WEIGHT_REVISION, + "model_safetensors_bytes": FULL_WEIGHT_BYTES, + "model_safetensors_sha256": FULL_WEIGHT_SHA256, + }, + }, + "no_cloud_evidence": { + "model_backend_is_local_openai_compatible": config.model_backend == "llama_cpp", + "hosted_backend_disabled_for_eval": config.model_backend != "hosted_omni", + "endpoint_models_probe_passed": endpoint_metadata.get("status") == "passed", + "route_smoke_counts_as_no_cloud_route_proof": bool( + smoke_evidence.get("counts_as_no_cloud_route_proof") + ), + "counts_as_50_case_local_llm_eval": bool( + local_evidence.get("counts_as_50_case_local_llm_eval") + ), + "counts_as_50_case_local_llm_competence": bool( + local_evidence.get("counts_as_50_case_local_llm_competence") + ), + "base_url_host": _base_url_host(config.llama_base_url), + "base_url_host_class": _base_url_host_class(config.llama_base_url), + "note": ( + "This manifest proves Figment used MODEL_BACKEND=llama_cpp against the configured " + "OpenAI-compatible endpoint. For LAN or other local hosts, keep runtime evidence beside " + "this bundle if judges need independent network-local attestation." + ), + }, + "score_summary": { + "total_cases": eval_summary.get("total_cases", len(records)), + "raw_configured_model_successes": eval_summary.get("raw_configured_model_successes", 0), + "repair_successes": eval_summary.get("repair_successes", 0), + "competence_successes": eval_summary.get("competence_successes", 0), + "fallback_uses": eval_summary.get("fallback_uses", 0), + "canned_fallback_uses": eval_summary.get("canned_fallback_uses", 0), + "final_validation_successes": eval_summary.get("final_validation_successes", 0), + "expected_label_successes": eval_summary.get("expected_label_successes"), + "expected_label_failures": eval_summary.get("expected_label_failures"), + }, + "case_ids": { + "raw_success": _case_ids(records, "raw_configured_model_success"), + "repair_success": _case_ids(records, "repair_success"), + "full_fallback": _case_ids(records, "canned_fallback_used"), + "competence_success": _case_ids(records, "competence_success"), + }, + "field_provenance": { + "records_with_field_provenance": eval_summary.get("records_with_field_provenance", 0), + "field_provenance_fields": eval_summary.get("field_provenance_fields", 0), + "field_provenance_counts": eval_summary.get("field_provenance_counts", {}), + "model_retained_field_count": eval_summary.get("model_retained_field_count", 0), + "visible_field_provenance_count": eval_summary.get("visible_field_provenance_count", 0), + "model_visible_field_count": eval_summary.get("model_visible_field_count", 0), + "deterministic_patch_count": eval_summary.get("deterministic_patch_count", 0), + "model_field_pass_rate": eval_summary.get("model_field_pass_rate", 0), + "model_visible_fields_retained": eval_summary.get("model_visible_fields_retained", 0), + }, + "latency_ms": _latency_summary(latency_values), + "trace_hash_count": len(trace_entries), + "trace_hashes": trace_entries, + "missing_trace_hash_case_ids": missing_trace_hash_case_ids, + } + + +def _read_eval_records(path: Path) -> list[dict[str, Any]]: + if not path.exists(): + return [] + records: list[dict[str, Any]] = [] + for line in path.read_text(encoding="utf-8").splitlines(): + if line.strip(): + records.append(json.loads(line)) + return records + + +def _file_sha256(path: Path) -> str | None: + if not path.exists(): + return None + digest = hashlib.sha256() + with path.open("rb") as handle: + for chunk in iter(lambda: handle.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +def _advertised_model_ids(endpoint_payload: dict[str, Any]) -> list[str]: + data = endpoint_payload.get("data") + if not isinstance(data, list): + return [] + ids: list[str] = [] + for item in data: + if isinstance(item, dict) and item.get("id"): + ids.append(str(item["id"])) + return ids + + +def _base_url_host(base_url: str) -> str | None: + return urllib.parse.urlsplit(base_url).hostname + + +def _base_url_host_class(base_url: str) -> str: + host = _base_url_host(base_url) + if not host: + return "unknown" + try: + address = ipaddress.ip_address(host) + except ValueError: + lowered = host.lower() + if lowered == "localhost" or lowered.endswith(".localhost"): + return "loopback" + if lowered.endswith(".local"): + return "mdns_local" + return "dns_name_unclassified" + if address.is_loopback: + return "loopback" + if address.is_private: + return "private_lan" + if address.is_link_local: + return "link_local" + return "public_or_unclassified_ip" + + +def _case_ids(records: list[dict[str, Any]], flag: str) -> list[str]: + return [str(record.get("case_id")) for record in records if record.get(flag)] + + +def _latency_summary(values: list[float]) -> dict[str, Any]: + if not values: + return { + "case_count": 0, + "min": None, + "mean": None, + "p50": None, + "p95": None, + "max": None, + } + sorted_values = sorted(values) + return { + "case_count": len(values), + "min": round(sorted_values[0], 3), + "mean": round(sum(sorted_values) / len(sorted_values), 3), + "p50": round(_percentile(sorted_values, 0.50), 3), + "p95": round(_percentile(sorted_values, 0.95), 3), + "max": round(sorted_values[-1], 3), + } + + +def _percentile(sorted_values: list[float], percentile: float) -> float: + if len(sorted_values) == 1: + return sorted_values[0] + index = percentile * (len(sorted_values) - 1) + lower = int(index) + upper = min(lower + 1, len(sorted_values) - 1) + fraction = index - lower + return sorted_values[lower] + (sorted_values[upper] - sorted_values[lower]) * fraction + + +@contextmanager +def _local_4b_env(base_url: str, model_id: str, timeout_seconds: float) -> Any: + overrides = { + "PYTHON_DOTENV_DISABLED": "true", + "FIGMENT_MODE": "local", + "MODEL_STACK": "local_4b_parakeet", + "MODEL_BACKEND": "llama_cpp", + "AUDIO_BACKEND": "none", + "LOCAL_MODEL_ID": model_id, + "LLAMA_BASE_URL": base_url, + "FIGMENT_SMOKE_ALLOW_NETWORK": "true", + "FIGMENT_MODEL_TIMEOUT_SECONDS": str(timeout_seconds), + } + previous = {key: os.environ.get(key) for key in overrides} + os.environ.update(overrides) + try: + yield + finally: + for key, value in previous.items(): + if value is None: + os.environ.pop(key, None) + else: + os.environ[key] = value + + +def _write_json(path: Path, payload: dict[str, Any]) -> None: + path.write_text(f"{json.dumps(payload, indent=2, sort_keys=True)}\n", encoding="utf-8") + + +def _default_output_dir() -> Path: + stamp = strftime("%Y%m%dT%H%M%SZ", gmtime()) + return Path("traces") / f"local_4b_evidence_{stamp}" + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--base-url", default=os.getenv("LLAMA_BASE_URL", DEFAULT_BASE_URL)) + parser.add_argument("--model-id", default=NVIDIA_NEMOTRON_3_NANO_4B_BF16_MODEL_ID) + parser.add_argument("--output-dir", type=Path, default=None) + parser.add_argument("--cases", action="append", default=None, help="JSONL eval case path. Repeatable.") + parser.add_argument("--limit", type=int, default=None) + parser.add_argument("--timeout-seconds", type=float, default=DEFAULT_TIMEOUT_SECONDS) + parser.add_argument("--smoke-only", action="store_true") + parser.add_argument("--force-eval", action="store_true") + args = parser.parse_args(argv) + + output_dir = args.output_dir or _default_output_dir() + case_paths = [Path(path) for path in args.cases] if args.cases else list(DEFAULT_CASE_PATHS) + summary = run_evidence( + base_url=args.base_url, + model_id=args.model_id, + output_dir=output_dir, + case_paths=case_paths, + limit=args.limit, + timeout_seconds=args.timeout_seconds, + smoke_only=args.smoke_only, + force_eval=args.force_eval, + ) + print(json.dumps(summary, indent=2, sort_keys=True)) + if summary["status"] in {"eval_completed", "smoke_passed"}: + return 0 + if summary["status"] == "endpoint_unavailable": + return 2 + return 1 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/run_local_asr_evidence.py b/scripts/run_local_asr_evidence.py new file mode 100644 index 0000000000000000000000000000000000000000..d0492e10c93cae45adbb7ef4f9e8c058f876e209 --- /dev/null +++ b/scripts/run_local_asr_evidence.py @@ -0,0 +1,322 @@ +#!/usr/bin/env python3 +"""Capture evidence for the local Parakeet ASR draft-intake path.""" + +from __future__ import annotations + +import argparse +from contextlib import suppress +import hashlib +import json +from pathlib import Path +import sys +from time import gmtime, strftime +from typing import Any +import wave + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from figment.audio_intake import draft_audio_intake # noqa: E402 +from figment.config import ( # noqa: E402 + FigmentConfig, + NVIDIA_NEMOTRON_3_NANO_4B_BF16_MODEL_ID, + PARAKEET_ASR_MODEL_ID, +) + + +PARAKEET_REPO = "nvidia/parakeet-rnnt-1.1b" +PARAKEET_REVISION = "a07b19e98a26c1873a3f2622c446a4a1ca6316cb" +PARAKEET_NEMO_BYTES = 4_283_105_280 +PARAKEET_NEMO_SHA256 = "535896f014953d945b287ac533560e20da8103c6781b152de4645528e2b60738" +PARAKEET_SNAPSHOT_PATH = Path( + "/Users/drake.thomsen/.cache/huggingface/hub/" + "models--nvidia--parakeet-rnnt-1.1b/snapshots/a07b19e98a26c1873a3f2622c446a4a1ca6316cb" +) +PARAKEET_NEMO_PATH = PARAKEET_SNAPSHOT_PATH / "parakeet-rnnt-1.1b.nemo" + + +def run_evidence( + *, + output_dir: Path, + provider_payload_path: Path | None = None, + audio_path: Path | None = None, + provider_note: str = "", +) -> dict[str, Any]: + output_dir.mkdir(parents=True, exist_ok=True) + artifact = _artifact_summary() + _write_json(output_dir / "artifact_metadata.json", artifact) + + audio_metadata = _audio_metadata(audio_path) if audio_path else None + if audio_metadata: + _write_json(output_dir / "audio_metadata.json", audio_metadata) + + summary: dict[str, Any] = { + "status": "artifact_missing" if not artifact["present"] else "artifact_present_provider_payload_required", + "output_dir": str(output_dir), + "artifact_metadata_path": str(output_dir / "artifact_metadata.json"), + "audio_metadata_path": str(output_dir / "audio_metadata.json") if audio_metadata else None, + "asr_evidence_manifest_path": str(output_dir / "asr_evidence_manifest.json"), + "provider_payload_path": str(provider_payload_path) if provider_payload_path else None, + "draft_path": None, + "provider_note": provider_note, + "raw_audio_stored": False, + "counts_as_local_asr_artifact": bool(artifact["present"]), + "counts_as_local_asr_proof": False, + } + if not artifact["present"] or provider_payload_path is None: + _write_json( + output_dir / "asr_evidence_manifest.json", + _asr_evidence_manifest( + artifact=artifact, + audio_metadata=audio_metadata, + provider_payload_metadata=None, + draft=None, + checks=None, + provider_note=provider_note, + ), + ) + _write_json(output_dir / "summary.json", summary) + return summary + + provider_payload = _read_json(provider_payload_path) + provider_payload_metadata = _provider_payload_metadata(provider_payload_path) + _write_json(output_dir / "provider_payload_metadata.json", provider_payload_metadata) + + config = FigmentConfig( + figment_mode="local", + model_stack="local_4b_parakeet", + model_backend="llama_cpp", + audio_backend="parakeet_nemo", + enable_audio_intake=True, + allow_local_asr=True, + local_model_id=NVIDIA_NEMOTRON_3_NANO_4B_BF16_MODEL_ID, + ).validated() + draft = draft_audio_intake(config=config, provider_payload=provider_payload) + draft_path = output_dir / "audio_draft.json" + _write_json(draft_path, draft) + checks = _draft_checks(draft) + _write_json(output_dir / "draft_checks.json", checks) + _write_json( + output_dir / "asr_evidence_manifest.json", + _asr_evidence_manifest( + artifact=artifact, + audio_metadata=audio_metadata, + provider_payload_metadata=provider_payload_metadata, + draft=draft, + checks=checks, + provider_note=provider_note, + config=config, + ), + ) + + summary.update( + { + "status": "local_asr_proof_passed" if checks["counts_as_local_asr_proof"] else "local_asr_proof_failed", + "draft_path": str(draft_path), + "draft_checks_path": str(output_dir / "draft_checks.json"), + "provider_payload_metadata_path": str(output_dir / "provider_payload_metadata.json"), + "counts_as_local_asr_proof": checks["counts_as_local_asr_proof"], + } + ) + _write_json(output_dir / "summary.json", summary) + return summary + + +def _artifact_summary() -> dict[str, Any]: + present = PARAKEET_NEMO_PATH.exists() + size = PARAKEET_NEMO_PATH.stat().st_size if present else None + sha256 = _sha256(PARAKEET_NEMO_PATH) if present else None + return { + "repo": PARAKEET_REPO, + "revision": PARAKEET_REVISION, + "snapshot_path": str(PARAKEET_SNAPSHOT_PATH), + "nemo_path": str(PARAKEET_NEMO_PATH), + "expected_nemo_bytes": PARAKEET_NEMO_BYTES, + "expected_nemo_sha256": PARAKEET_NEMO_SHA256, + "present": present, + "nemo_bytes": size, + "nemo_sha256": sha256, + "matches_expected": present and size == PARAKEET_NEMO_BYTES and sha256 == PARAKEET_NEMO_SHA256, + } + + +def _audio_metadata(audio_path: Path) -> dict[str, Any]: + metadata: dict[str, Any] = { + "path": str(audio_path), + "exists": audio_path.exists(), + "raw_audio_copied_to_evidence": False, + } + if not audio_path.exists(): + return metadata + metadata.update( + { + "bytes": audio_path.stat().st_size, + "sha256": _sha256(audio_path), + } + ) + with suppress(wave.Error, OSError): + with wave.open(str(audio_path), "rb") as wav: + frames = wav.getnframes() + rate = wav.getframerate() + metadata.update( + { + "channels": wav.getnchannels(), + "sample_rate_hz": rate, + "duration_seconds": round(frames / rate, 3) if rate else None, + } + ) + return metadata + + +def _provider_payload_metadata(path: Path) -> dict[str, Any]: + return { + "path": str(path), + "bytes": path.stat().st_size, + "sha256": _sha256(path), + } + + +def _draft_checks(draft: dict[str, Any]) -> dict[str, Any]: + checks = { + "has_transcript": bool(str(draft.get("transcript", "")).strip()), + "has_suggested_fields": bool(draft.get("suggested_fields")), + "audio_intake_path_is_parakeet": draft.get("audio_intake_path") == "parakeet_rnnt_plus_text_nemotron", + "audio_runtime_is_local_4b": draft.get("audio_runtime") == "local_4b_parakeet", + "audio_model_is_parakeet": draft.get("audio_model_id") == PARAKEET_ASR_MODEL_ID, + "field_fill_model_is_4b": draft.get("field_fill_model_id") == NVIDIA_NEMOTRON_3_NANO_4B_BF16_MODEL_ID, + "transcript_source_is_local_parakeet": draft.get("transcript_source") == "local_parakeet_asr_provider", + "audio_source_is_local_parakeet": draft.get("audio_source") == "local_parakeet_asr_payload", + "requires_confirmation": draft.get("confirmed_intake_required") is True, + "is_unconfirmed": draft.get("confirmation_status") == "unconfirmed", + "raw_audio_stored_false": draft.get("raw_audio_stored") is False, + } + proof = all(checks.values()) + return {"checks": checks, "counts_as_local_asr_proof": proof} + + +def _asr_evidence_manifest( + *, + artifact: dict[str, Any], + audio_metadata: dict[str, Any] | None, + provider_payload_metadata: dict[str, Any] | None, + draft: dict[str, Any] | None, + checks: dict[str, Any] | None, + provider_note: str, + config: FigmentConfig | None = None, +) -> dict[str, Any]: + return { + "evidence_version": 1, + "artifact": artifact, + "provider_payload": provider_payload_metadata, + "provider_note": provider_note, + "configured_route": _configured_route_summary(config), + "raw_audio_handling": { + "audio_metadata_present": audio_metadata is not None, + "audio_metadata_sha256": audio_metadata.get("sha256") if audio_metadata else None, + "raw_audio_copied_to_evidence": False, + "raw_audio_stored": bool(draft.get("raw_audio_stored")) if draft else False, + }, + "draft_summary": _draft_summary(draft), + "draft_checks": checks, + "proof_flags": { + "counts_as_local_asr_artifact": bool(artifact.get("present")), + "counts_as_local_asr_proof": bool(checks and checks.get("counts_as_local_asr_proof")), + }, + } + + +def _configured_route_summary(config: FigmentConfig | None) -> dict[str, Any]: + if config is None: + return { + "figment_mode": "local", + "model_stack": "local_4b_parakeet", + "model_backend": "llama_cpp", + "audio_backend": "parakeet_nemo", + "text_model_id": NVIDIA_NEMOTRON_3_NANO_4B_BF16_MODEL_ID, + "audio_model_id": PARAKEET_ASR_MODEL_ID, + } + return { + "figment_mode": config.figment_mode, + "model_stack": config.model_stack, + "model_backend": config.model_backend, + "audio_backend": config.audio_backend, + "text_model_id": config.local_model_id, + "audio_model_id": config.audio_model_id, + } + + +def _draft_summary(draft: dict[str, Any] | None) -> dict[str, Any] | None: + if draft is None: + return None + transcript = str(draft.get("transcript") or "") + suggested_fields = draft.get("suggested_fields") + missing_or_unclear_fields = draft.get("missing_or_unclear_fields") + provisional_red_flags = draft.get("provisional_red_flag_mentions") + return { + "audio_intake_path": draft.get("audio_intake_path"), + "audio_runtime": draft.get("audio_runtime"), + "transcript_source": draft.get("transcript_source"), + "audio_source": draft.get("audio_source"), + "confirmation_status": draft.get("confirmation_status"), + "transcript_hash": hashlib.sha256(transcript.encode("utf-8")).hexdigest() if transcript else None, + "transcript_char_count": len(transcript), + "suggested_field_count": len(suggested_fields) if isinstance(suggested_fields, list) else 0, + "missing_or_unclear_field_count": ( + len(missing_or_unclear_fields) if isinstance(missing_or_unclear_fields, list) else 0 + ), + "provisional_red_flag_mention_count": ( + len(provisional_red_flags) if isinstance(provisional_red_flags, list) else 0 + ), + "raw_audio_stored": draft.get("raw_audio_stored"), + } + + +def _read_json(path: Path) -> dict[str, Any]: + payload = json.loads(path.read_text(encoding="utf-8")) + if not isinstance(payload, dict): + raise ValueError("provider payload must be a JSON object") + return payload + + +def _sha256(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as file: + for chunk in iter(lambda: file.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +def _write_json(path: Path, payload: dict[str, Any]) -> None: + path.write_text(f"{json.dumps(payload, indent=2, sort_keys=True)}\n", encoding="utf-8") + + +def _default_output_dir() -> Path: + stamp = strftime("%Y%m%dT%H%M%SZ", gmtime()) + return Path("traces") / f"local_asr_parakeet_evidence_{stamp}" + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--provider-payload", type=Path, default=None) + parser.add_argument("--audio", type=Path, default=None, help="Optional source audio path; metadata only, not copied.") + parser.add_argument("--provider-note", default="") + parser.add_argument("--output-dir", type=Path, default=None) + args = parser.parse_args(argv) + + summary = run_evidence( + output_dir=args.output_dir or _default_output_dir(), + provider_payload_path=args.provider_payload, + audio_path=args.audio, + provider_note=args.provider_note, + ) + print(json.dumps(summary, indent=2, sort_keys=True)) + if summary["counts_as_local_asr_proof"]: + return 0 + if summary["counts_as_local_asr_artifact"]: + return 2 + return 1 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/summarize_v7_corpus_needs.py b/scripts/summarize_v7_corpus_needs.py new file mode 100644 index 0000000000000000000000000000000000000000..6b38eac467e4c5402f6c18d8deb3465eae9235f9 --- /dev/null +++ b/scripts/summarize_v7_corpus_needs.py @@ -0,0 +1,87 @@ +"""Summarize v6 eval failures that should shape the Figment v7 corpus.""" + +from __future__ import annotations + +import argparse +from collections import Counter +import json +from pathlib import Path +from typing import Any + + +def main() -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--eval-jsonl", type=Path, required=True) + parser.add_argument("--output", type=Path, required=True) + args = parser.parse_args() + + summary = summarize_eval(args.eval_jsonl) + args.output.parent.mkdir(parents=True, exist_ok=True) + args.output.write_text(json.dumps(summary, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(summary, indent=2, sort_keys=True)) + return 0 + + +def summarize_eval(eval_jsonl: Path) -> dict[str, Any]: + records = _read_jsonl(eval_jsonl) + deterministic_patch_field_counts: Counter[str] = Counter() + expected_label_check_failures: Counter[str] = Counter() + competence_failure_case_ids: list[str] = [] + expected_label_failure_case_ids: list[str] = [] + missing_source_card_ids_by_case: dict[str, list[str]] = {} + deterministic_patch_fields_by_case: dict[str, list[str]] = {} + actual_source_card_sets_for_failures: dict[str, list[str]] = {} + + for record in records: + case_id = str(record.get("case_id") or "") + patch_fields = _string_list(record.get("deterministic_scaffold_patched_fields")) + for field in patch_fields: + deterministic_patch_field_counts[field] += 1 + if patch_fields: + deterministic_patch_fields_by_case[case_id] = patch_fields + + expected_score = record.get("expected_label_score") if isinstance(record.get("expected_label_score"), dict) else {} + for key, value in expected_score.items(): + if isinstance(value, bool) and value is False: + expected_label_check_failures[key] += 1 + + if record.get("competence_success") is not True: + competence_failure_case_ids.append(case_id) + actual_source_card_sets_for_failures[case_id] = _string_list(record.get("actual_source_card_ids")) + + if expected_score.get("all_expected_labels_passed") is not True: + expected_label_failure_case_ids.append(case_id) + missing_source_card_ids = _string_list(expected_score.get("missing_expected_source_card_ids")) + if missing_source_card_ids: + missing_source_card_ids_by_case[case_id] = missing_source_card_ids + actual_source_card_sets_for_failures[case_id] = _string_list(record.get("actual_source_card_ids")) + + return { + "total_cases": len(records), + "competence_failure_case_ids": competence_failure_case_ids, + "competence_failure_count": len(competence_failure_case_ids), + "expected_label_failure_case_ids": expected_label_failure_case_ids, + "expected_label_failure_count": len(expected_label_failure_case_ids), + "expected_label_check_failures": dict(sorted(expected_label_check_failures.items())), + "missing_source_card_ids_by_case": missing_source_card_ids_by_case, + "missing_source_card_id_counts": dict( + sorted(Counter(card_id for cards in missing_source_card_ids_by_case.values() for card_id in cards).items()) + ), + "deterministic_patch_fields_by_case": deterministic_patch_fields_by_case, + "deterministic_patch_field_counts": dict(sorted(deterministic_patch_field_counts.items())), + "actual_source_card_sets_for_failures": actual_source_card_sets_for_failures, + } + + +def _read_jsonl(path: Path) -> list[dict[str, Any]]: + return [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()] + + +def _string_list(value: Any) -> list[str]: + if not isinstance(value, list): + return [] + return [str(item) for item in value if str(item).strip()] + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/verify_finetune_harness_alignment.py b/scripts/verify_finetune_harness_alignment.py new file mode 100644 index 0000000000000000000000000000000000000000..66f76f90ff3a7a1e8a1d91d66cec249657d0cc91 --- /dev/null +++ b/scripts/verify_finetune_harness_alignment.py @@ -0,0 +1,585 @@ +"""Verify Figment SFT rows match the local 4B navigator harness.""" + +from __future__ import annotations + +import argparse +from collections import Counter +import json +from pathlib import Path +import sys +from typing import Any + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +if str(PROJECT_ROOT) not in sys.path: + sys.path.insert(0, str(PROJECT_ROOT)) + +from figment.focused_repair import build_focused_repair_prompts # noqa: E402 +from figment.harness_evidence import build_harness_evidence # noqa: E402 +from figment.observation_targets import required_observation_targets # noqa: E402 +from figment.eval_metrics import score_expected_labels # noqa: E402 +from figment.prompt_builder import build_prompt # noqa: E402 +from figment.retrieval import known_card_ids # noqa: E402 +from figment.retrieval import load_protocol_cards # noqa: E402 +from figment.retrieval import query_from_intake # noqa: E402 +from figment.retrieval import search_protocol_cards # noqa: E402 +from figment.rules import run_red_flag_checks # noqa: E402 +from figment.validators import urgency_floor_from_rules # noqa: E402 +from figment.validators import validate_navigator_output # noqa: E402 +from scripts.augment_finetune_repair_rows import _corrupt_output # noqa: E402 +from scripts.augment_finetune_repair_rows import _extra_failures_for_scope # noqa: E402 +from scripts.generate_finetune_data import forbidden_behavior_for_version # noqa: E402 +from scripts.generate_finetune_data import ensure_retrieved_cards # noqa: E402 +from scripts.generate_finetune_data import _required_retrieved_ids # noqa: E402 +from scripts.generate_finetune_data import uses_v5_focused_policy # noqa: E402 +from scripts.generate_finetune_data import uses_v6_observation_policy # noqa: E402 +from scripts.generate_finetune_data import uses_v7_source_card_policy # noqa: E402 +from scripts.generate_finetune_data import v2_policy_issues # noqa: E402 +from scripts.generate_finetune_data import v3_policy_issues # noqa: E402 +from scripts.generate_finetune_data import v5_policy_issues # noqa: E402 +from scripts.generate_finetune_data import v6_policy_issues # noqa: E402 +from scripts.generate_finetune_data import v7_source_card_closure_issues # noqa: E402 +from scripts.generate_finetune_data import uses_v3_field_workflow_policy # noqa: E402 + + +DEFAULT_DATASET = Path("data/finetune/figment_sft_v1.jsonl") +DEFAULT_CASE_SPECS = Path("data/finetune/figment_sft_v1_case_specs.jsonl") +ALLOWED_FACT_SOURCES = {"structured_field", "responder_note", "protocol_card"} + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--dataset", type=Path, default=DEFAULT_DATASET) + parser.add_argument("--case-specs", type=Path, default=DEFAULT_CASE_SPECS) + args = parser.parse_args(argv) + + summary = verify_rows(dataset_path=args.dataset, case_specs_path=args.case_specs) + print(json.dumps(summary, indent=2, sort_keys=True)) + return 0 if summary["passed"] else 1 + + +def verify_rows(*, dataset_path: Path, case_specs_path: Path) -> dict[str, Any]: + rows = _read_jsonl(dataset_path) + specs = {str(item["case_id"]): item for item in _read_jsonl(case_specs_path)} + rows_by_id = {str(row.get("case_id")): row for row in rows} + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + issues: list[dict[str, Any]] = [] + categories: Counter[str] = Counter() + task_types: Counter[str] = Counter() + + for row_number, row in enumerate(rows, start=1): + case_id = str(row.get("case_id", "")) + categories[str(row.get("category", ""))] += 1 + task_type = str(row.get("metadata", {}).get("task_type", "navigator_full")) + task_types[task_type] += 1 + base_case_id = str(row.get("metadata", {}).get("base_case_id") or case_id) + spec = specs.get(base_case_id) + if spec is None: + issues.append(_issue(row_number, case_id, "missing_case_spec")) + continue + dataset_version = str(row.get("version") or spec.get("dataset_version") or "figment_sft_v1") + + messages = row.get("messages") + if not isinstance(messages, list) or [item.get("role") for item in messages] != ["user", "assistant"]: + issues.append(_issue(row_number, case_id, "messages_must_match_llama_cpp_user_assistant_shape")) + continue + + intake = spec["structured_intake"] + rule_results = [rule.to_dict() for rule in run_red_flag_checks(intake)] + floor = urgency_floor_from_rules(rule_results) + retrieved = search_protocol_cards(query_from_intake(intake), limit=6) + spec_dataset_version = str(spec.get("dataset_version") or dataset_version) + if uses_v7_source_card_policy(spec_dataset_version): + synthetic_spec = type( + "SyntheticSpecForVerification", + (), + { + "target_protocol_card_id": str(spec.get("target_protocol_card_id") or ""), + "dataset_version": spec_dataset_version, + }, + )() + retrieved = ensure_retrieved_cards( + retrieved, + required_ids=_required_retrieved_ids(synthetic_spec, rule_results), + cards_by_id=cards_by_id, + limit=6, + ) + retrieved_ids = [str(item.get("card_id", "")) for item in retrieved if item.get("card_id")] + harness_prompt, prompt_hash = build_prompt(intake, retrieved, rule_results, floor) + expected_user_prompt = harness_prompt + + try: + output = json.loads(str(messages[1].get("content", ""))) + except json.JSONDecodeError as exc: + issues.append(_issue(row_number, case_id, "assistant_content_is_not_json", error=str(exc))) + continue + + output_text = json.dumps(output, sort_keys=True) + lowered_output_text = output_text.lower() + if " list[dict[str, Any]]: + return [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()] + + +def _issue(row_number: int, case_id: str, issue_type: str, **details: Any) -> dict[str, Any]: + return {"row_number": row_number, "case_id": case_id, "type": issue_type, **details} + + +def _append_v5_metadata_issues( + issues: list[dict[str, Any]], + *, + row_number: int, + case_id: str, + row: dict[str, Any], + output: dict[str, Any], +) -> None: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + if metadata.get("dataset_version") != "figment_sft_v5": + issues.append(_issue(row_number, case_id, "v5_metadata_dataset_version_missing")) + if metadata.get("training_focus") != row.get("category"): + issues.append( + _issue( + row_number, + case_id, + "v5_metadata_training_focus_mismatch", + training_focus=metadata.get("training_focus"), + category=row.get("category"), + ) + ) + excluded = metadata.get("excluded_eval_case_ids") + if not isinstance(excluded, list) or not { + "field_workflow_holdout_v1-000054", + "field_workflow_holdout_v1-000099", + } <= {str(item) for item in excluded}: + issues.append(_issue(row_number, case_id, "v5_metadata_excluded_eval_case_ids_missing")) + + source_cards = set(_string_list(output.get("source_cards"))) + missing_source = [card_id for card_id in _string_list(metadata.get("must_include_source_cards")) if card_id not in source_cards] + if missing_source: + issues.append(_issue(row_number, case_id, "v5_metadata_must_include_source_cards_missing", missing=missing_source)) + + required_selected_ids = _string_list(metadata.get("must_include_selected_required_observation_ids")) + selected_ids = set(_string_list(output.get("selected_required_observation_ids"))) + missing_selected = [target_id for target_id in required_selected_ids if target_id not in selected_ids] + if missing_selected: + issues.append( + _issue( + row_number, + case_id, + "v5_metadata_must_include_selected_required_observation_ids_missing", + missing=missing_selected, + ) + ) + + +def _append_v6_metadata_issues( + issues: list[dict[str, Any]], + *, + row_number: int, + case_id: str, + row: dict[str, Any], + output: dict[str, Any], +) -> None: + metadata = row.get("metadata") if isinstance(row.get("metadata"), dict) else {} + dataset_version = str(metadata.get("dataset_version") or row.get("version") or "") + if not dataset_version.startswith("figment_sft_v6"): + issues.append(_issue(row_number, case_id, "v6_metadata_dataset_version_missing")) + if metadata.get("training_focus") != row.get("category"): + issues.append( + _issue( + row_number, + case_id, + "v6_metadata_training_focus_mismatch", + training_focus=metadata.get("training_focus"), + category=row.get("category"), + ) + ) + if metadata.get("v6_training_policy_version") != 1: + issues.append(_issue(row_number, case_id, "v6_metadata_policy_version_missing")) + + required_targets = metadata.get("required_observation_targets") + if not isinstance(required_targets, list): + issues.append(_issue(row_number, case_id, "v6_metadata_required_observation_targets_missing")) + + forbidden_cues = metadata.get("harness_metadata_cues_not_observations") + if not isinstance(forbidden_cues, list) or "source card ids" not in {str(item).lower() for item in forbidden_cues}: + issues.append(_issue(row_number, case_id, "v6_metadata_harness_cues_missing")) + + required_selected_ids = _string_list(metadata.get("must_include_selected_required_observation_ids")) + selected_ids = set(_string_list(output.get("selected_required_observation_ids"))) + missing_selected = [target_id for target_id in required_selected_ids if target_id not in selected_ids] + if missing_selected: + issues.append( + _issue( + row_number, + case_id, + "v6_metadata_must_include_selected_required_observation_ids_missing", + missing=missing_selected, + ) + ) + + +def _string_list(value: Any) -> list[str]: + if isinstance(value, list): + return [str(item) for item in value if str(item)] + return [] + + +def _candidate_ids(value: Any) -> list[str]: + if not isinstance(value, list): + return [] + ids = [] + for item in value: + if isinstance(item, dict) and item.get("card_id"): + ids.append(str(item["card_id"])) + return ids + + +def _forbidden_behavior_for_dataset_version(dataset_version: str) -> list[str]: + return forbidden_behavior_for_version(dataset_version) + + +def _stable_hash_content(value: str) -> str: + from figment.trace import stable_hash + + return stable_hash(value) + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/tests/test_corrected_holdout_scoring.py b/tests/test_corrected_holdout_scoring.py new file mode 100644 index 0000000000000000000000000000000000000000..9feb34ab558912a9af26f4e971bb184369f3e4d9 --- /dev/null +++ b/tests/test_corrected_holdout_scoring.py @@ -0,0 +1,25 @@ +import json +from pathlib import Path + +from scripts.build_corrected_field_workflow_holdout import build_corrected_view + + +def test_corrected_holdout_scoring_removes_negated_chest_pain_labels(tmp_path: Path) -> None: + output = tmp_path / "field_workflow_holdout_v1_corrected_scoring.jsonl" + manifest = tmp_path / "field_workflow_holdout_v1_corrected_scoring_manifest.json" + + result = build_corrected_view( + input_path=Path("data/eval/field_workflow_holdout_v1.jsonl"), + output_path=output, + manifest_path=manifest, + ) + + rows = [json.loads(line) for line in output.read_text(encoding="utf-8").splitlines()] + by_id = {row["case_id"]: row for row in rows} + + assert result["row_count"] == 150 + assert by_id["field_workflow_holdout_v1-000050"]["expected_red_flag_rule_ids"] == [] + assert by_id["field_workflow_holdout_v1-000050"]["expected_min_protocol_urgency"] == "routine" + assert "CHEST-PAIN-ESCALATION-v1" not in by_id["field_workflow_holdout_v1-000050"]["expected_source_card_ids"] + assert "red_flag_chest_pain" not in by_id["field_workflow_holdout_v1-000019"]["expected_red_flag_rule_ids"] + assert manifest.exists() diff --git a/tests/test_evidence_gate_status.py b/tests/test_evidence_gate_status.py new file mode 100644 index 0000000000000000000000000000000000000000..781a30f676d7d2134ce7794ed402ef700d53ae64 --- /dev/null +++ b/tests/test_evidence_gate_status.py @@ -0,0 +1,83 @@ +import json +from pathlib import Path + +from scripts import evidence_gate_status + + +def test_current_repo_report_keeps_remaining_external_gates_incomplete() -> None: + report = evidence_gate_status.build_report() + + assert report["status"] == "incomplete" + assert report["ready_for_badge_claims"] is False + assert report["gates"]["claim_audit"]["passed"] is True + assert report["gates"]["local_4b_50_case_eval"]["passed"] is False + assert report["gates"]["no_cloud_route"]["passed"] is False + assert report["gates"]["llama_champion_route"]["passed"] is False + assert report["gates"]["local_asr_provider_proof"]["passed"] is False + assert report["gates"]["trained_responder_user_test"]["passed"] is False + assert "local_4b_50_case_eval" in report["missing_gate_keys"] + assert "no_cloud_route" in report["missing_gate_keys"] + assert "llama_champion_route" in report["missing_gate_keys"] + assert "local_asr_provider_proof" in report["missing_gate_keys"] + assert "local full-weight endpoint" in report["gates"]["local_4b_50_case_eval"]["next_action"] + assert "real local Parakeet provider payload" in report["gates"]["local_asr_provider_proof"]["next_action"] + + +def test_report_uses_local_evidence_artifacts_when_present(tmp_path: Path) -> None: + local_4b_dir = tmp_path / "traces/local_4b_evidence_20260607T000000Z" + local_4b_dir.mkdir(parents=True) + (local_4b_dir / "summary.json").write_text( + json.dumps( + { + "status": "eval_completed", + "total_cases": 50, + "counts_as_no_cloud_route_proof": True, + "counts_as_50_case_local_llm_competence": True, + } + ), + encoding="utf-8", + ) + (local_4b_dir / "eval_evidence_manifest.json").write_text("{}", encoding="utf-8") + asr_dir = tmp_path / "traces/local_asr_parakeet_evidence_20260607T000000Z" + asr_dir.mkdir(parents=True) + (asr_dir / "summary.json").write_text( + json.dumps( + { + "status": "local_asr_proof_passed", + "counts_as_local_asr_artifact": True, + "counts_as_local_asr_proof": True, + } + ), + encoding="utf-8", + ) + (asr_dir / "asr_evidence_manifest.json").write_text("{}", encoding="utf-8") + docs = tmp_path / "docs" + docs.mkdir() + (docs / "submission_checklist.md").write_text( + "\n".join( + [ + "| Demo video | Proof needed | Pending |", + "| Social post | Proof needed | Pending |", + ] + ), + encoding="utf-8", + ) + (docs / "user_test_notes.md").write_text( + "Status: template only. No completed user-test results are recorded here yet.", + encoding="utf-8", + ) + (docs / "model_parameter_evidence_ledger.md").write_text( + "4B Figment adapter stretch: Not trained, published, or measured in this ledger.", + encoding="utf-8", + ) + + report = evidence_gate_status.build_report(tmp_path) + + assert report["gates"]["local_4b_50_case_eval"]["passed"] is True + assert report["gates"]["no_cloud_route"]["passed"] is True + assert report["gates"]["llama_champion_route"]["passed"] is True + assert report["gates"]["local_asr_provider_proof"]["passed"] is True + assert str(local_4b_dir / "eval_evidence_manifest.json") in report["gates"]["local_4b_50_case_eval"]["evidence_paths"] + assert str(asr_dir / "asr_evidence_manifest.json") in report["gates"]["local_asr_provider_proof"]["evidence_paths"] + assert report["status"] == "incomplete" + assert "trained_responder_user_test" in report["missing_gate_keys"] diff --git a/tests/test_finetune_v10_data_plan.py b/tests/test_finetune_v10_data_plan.py new file mode 100644 index 0000000000000000000000000000000000000000..3a24dd2b3731a0dac4dcd096f7e01739c11d15f0 --- /dev/null +++ b/tests/test_finetune_v10_data_plan.py @@ -0,0 +1,140 @@ +import json +from collections import Counter + + +def _accepted_v10_row(): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import assemble_teacher_navigator_output + from scripts.generate_finetune_data import build_sft_row + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + from scripts.generate_finetune_data import score_candidate + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(0, cards_by_id, dataset_version="figment_sft_v10_delta") + prepared = prepare_case(spec, cards_by_id) + candidate = assemble_teacher_navigator_output( + prepared, + { + "facts": ["postpartum fever confirmed", "temperature elevated", "blood pressure pending"], + "missing": [ + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + ], + "observe": ["temperature if available", "bleeding report", "abdominal pain report"], + "checklist": ["cite fever and pregnancy danger-sign cards"], + "uncertain": ["blood pressure pending"], + "sbar": { + "situation": "postpartum fever", + "background": "postpartum field intake", + "assessment_observations_only": "fever and postpartum context confirmed", + "handoff_request": "request protocol review", + }, + "script": "I am checking fever and postpartum danger-sign observations.", + }, + ) + result = score_candidate(candidate, prepared) + assert result.passed is True, result.reward_components + row = build_sft_row( + prepared=prepared, + result=result, + teacher_model_id="teacher-test", + candidate_total=1, + candidate_passed=1, + ) + return row, case_spec_record(prepared) + + +def test_v10_failure_cycle_targets_v9_scaffold_dependence_gap(): + from scripts.generate_finetune_data import V10_NAVIGATOR_COUNTS + from scripts.generate_finetune_data import _failure_class_for_index + + categories = Counter( + _failure_class_for_index(index, dataset_version="figment_sft_v10_delta") + for index in range(sum(V10_NAVIGATOR_COUNTS.values())) + ) + first_twelve = { + _failure_class_for_index(index, dataset_version="figment_sft_v10_delta") + for index in range(12) + } + + assert categories == V10_NAVIGATOR_COUNTS + assert { + "postpartum_fever_required_obs_dual_field_closure", + "postpartum_fever_required_obs_candidate_focus", + } <= first_twelve + + +def test_v10_sft_row_requires_dual_field_fever_and_preg_observation_text(): + row, spec_record = _accepted_v10_row() + output = json.loads(row["messages"][1]["content"]) + metadata = row["metadata"] + selected_ids = set(output["selected_required_observation_ids"]) + + assert row["version"] == "figment_sft_v10_delta" + assert spec_record["dataset_version"] == "figment_sft_v10_delta" + assert spec_record["target_protocol_card_id"] == "FEVER-RED-FLAGS-v1" + assert {"PREG-001", "FEVER-001"} <= set(spec_record["expected_red_flag_rule_ids"]) + assert "PREG-DANGER-SIGNS-v1" in output["source_cards"] + assert "FEVER-RED-FLAGS-v1" in output["source_cards"] + assert [item["card_id"] for item in output["candidate_protocol_pathways"]] == [ + "FEVER-RED-FLAGS-v1", + "PREG-DANGER-SIGNS-v1", + ] + assert any(item.startswith("FEVER-RED-FLAGS-v1::required_observation::") for item in selected_ids) + assert any(item.startswith("PREG-DANGER-SIGNS-v1::required_observation::") for item in selected_ids) + assert set(metadata["must_include_selected_required_observation_ids"]) <= selected_ids + + for field in ("missing_info_to_collect", "next_observations_to_collect"): + observation_text = json.dumps(output[field]).lower() + for cue in ( + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + ): + assert cue in observation_text + + +def test_v10_full_corpus_wrapper_pins_delta_defaults(): + from scripts.generate_v10_full_corpus import DEFAULT_NAVIGATOR_COUNT + from scripts.generate_v10_full_corpus import DEFAULT_OUTPUT_VERSION + from scripts.generate_v10_full_corpus import DEFAULT_REPAIR_COUNT + from scripts.generate_v10_full_corpus import DEFAULT_TEACHER_MODEL_ID + from scripts.generate_v10_full_corpus import build_corpus_args + from scripts.merge_v10_training_corpus import build_merge_args + + assert DEFAULT_OUTPUT_VERSION == "figment_sft_v10_delta" + assert DEFAULT_TEACHER_MODEL_ID == "nvidia/nemotron-3-ultra-550b-a55b:free" + assert DEFAULT_NAVIGATOR_COUNT == 800 + assert DEFAULT_REPAIR_COUNT == 0 + args = build_corpus_args(["--navigator-count", "8", "--repair-count", "0", "--dry-run"]) + assert args[args.index("--navigator-count") + 1] == "8" + assert args[args.index("--repair-count") + 1] == "0" + assert args[-1] == "--dry-run" + + merge_args = build_merge_args(["--skip-verify"]) + assert merge_args[merge_args.index("--dataset-version") + 1] == "figment_sft_v10" + assert merge_args[merge_args.index("--base") + 1] == "data/finetune/figment_sft_v9.jsonl" + assert "--skip-verify" in merge_args diff --git a/tests/test_finetune_v11_data_plan.py b/tests/test_finetune_v11_data_plan.py new file mode 100644 index 0000000000000000000000000000000000000000..cc67e4d50a51d34f8c53d93caf03302d41e8e916 --- /dev/null +++ b/tests/test_finetune_v11_data_plan.py @@ -0,0 +1,139 @@ +import json +from collections import Counter + + +def _accepted_v11_row(): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import assemble_teacher_navigator_output + from scripts.generate_finetune_data import build_sft_row + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + from scripts.generate_finetune_data import score_candidate + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(0, cards_by_id, dataset_version="figment_sft_v11_delta") + prepared = prepare_case(spec, cards_by_id) + candidate = assemble_teacher_navigator_output( + prepared, + { + "facts": ["postpartum fever confirmed", "temperature elevated", "blood pressure pending"], + "missing": [ + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + ], + "observe": ["temperature if available", "bleeding report", "abdominal pain report"], + "checklist": ["cite fever and pregnancy danger-sign cards"], + "uncertain": ["blood pressure pending"], + "sbar": { + "situation": "postpartum fever", + "background": "postpartum field intake", + "assessment_observations_only": "fever and postpartum context confirmed", + "handoff_request": "request protocol review", + }, + "script": "I am checking fever and postpartum danger-sign observations.", + }, + ) + result = score_candidate(candidate, prepared) + assert result.passed is True, result.reward_components + row = build_sft_row( + prepared=prepared, + result=result, + teacher_model_id="teacher-test", + candidate_total=1, + candidate_passed=1, + ) + return row, case_spec_record(prepared) + + +def test_v11_failure_cycle_targets_v10_visible_observation_gap(): + from scripts.generate_finetune_data import V11_NAVIGATOR_COUNTS + from scripts.generate_finetune_data import _failure_class_for_index + + categories = Counter( + _failure_class_for_index(index, dataset_version="figment_sft_v11_delta") + for index in range(sum(V11_NAVIGATOR_COUNTS.values())) + ) + first_twelve = { + _failure_class_for_index(index, dataset_version="figment_sft_v11_delta") + for index in range(12) + } + + assert categories == V11_NAVIGATOR_COUNTS + assert { + "postpartum_fever_required_obs_visible_dual_field_holdout_shape", + "postpartum_fever_required_obs_dual_field_closure", + "postpartum_fever_required_obs_candidate_focus", + } <= first_twelve + + +def test_v11_sft_row_front_loads_pregnancy_danger_sign_text_in_both_fields(): + row, spec_record = _accepted_v11_row() + output = json.loads(row["messages"][1]["content"]) + metadata = row["metadata"] + selected_ids = set(output["selected_required_observation_ids"]) + + assert row["version"] == "figment_sft_v11_delta" + assert spec_record["dataset_version"] == "figment_sft_v11_delta" + assert spec_record["failure_class"] == "postpartum_fever_required_obs_visible_dual_field_holdout_shape" + assert "PREG-DANGER-SIGNS-v1" in output["source_cards"] + assert "FEVER-RED-FLAGS-v1" in output["source_cards"] + assert set(metadata["must_include_selected_required_observation_ids"]) <= selected_ids + + missing_text = json.dumps(output["missing_info_to_collect"]).lower() + observe_text = json.dumps(output["next_observations_to_collect"]).lower() + for cue in ( + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + ): + assert cue in missing_text + assert cue in observe_text + + first_missing = json.dumps(output["missing_info_to_collect"][:6]).lower() + assert "bleeding report" in first_missing + assert "seizure or fainting report" in first_missing + + +def test_v11_full_corpus_wrapper_pins_delta_defaults(): + from scripts.generate_v11_full_corpus import DEFAULT_NAVIGATOR_COUNT + from scripts.generate_v11_full_corpus import DEFAULT_OUTPUT_VERSION + from scripts.generate_v11_full_corpus import DEFAULT_REPAIR_COUNT + from scripts.generate_v11_full_corpus import DEFAULT_TEACHER_MODEL_ID + from scripts.generate_v11_full_corpus import build_corpus_args + from scripts.merge_v11_training_corpus import build_merge_args + + assert DEFAULT_OUTPUT_VERSION == "figment_sft_v11_delta" + assert DEFAULT_TEACHER_MODEL_ID == "nvidia/nemotron-3-ultra-550b-a55b:free" + assert DEFAULT_NAVIGATOR_COUNT == 800 + assert DEFAULT_REPAIR_COUNT == 0 + args = build_corpus_args(["--navigator-count", "8", "--repair-count", "0", "--dry-run"]) + assert args[args.index("--navigator-count") + 1] == "8" + assert args[args.index("--repair-count") + 1] == "0" + assert args[-1] == "--dry-run" + + merge_args = build_merge_args(["--skip-verify"]) + assert merge_args[merge_args.index("--dataset-version") + 1] == "figment_sft_v11" + assert merge_args[merge_args.index("--base") + 1] == "data/finetune/figment_sft_v10.jsonl" + assert "--skip-verify" in merge_args diff --git a/tests/test_finetune_v12_data_plan.py b/tests/test_finetune_v12_data_plan.py new file mode 100644 index 0000000000000000000000000000000000000000..fe598bb988e7d148ba41f8cb8aa99407b583b3c9 --- /dev/null +++ b/tests/test_finetune_v12_data_plan.py @@ -0,0 +1,171 @@ +import json +from collections import Counter + + +def _first_index_for_failure_class(failure_class: str) -> int: + from scripts.generate_finetune_data import V12_NAVIGATOR_COUNTS + from scripts.generate_finetune_data import _failure_class_for_index + + for index in range(sum(V12_NAVIGATOR_COUNTS.values())): + if _failure_class_for_index(index, dataset_version="figment_sft_v12_delta") == failure_class: + return index + raise AssertionError(f"missing v12 failure class: {failure_class}") + + +def _accepted_v12_row(failure_class: str): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import assemble_teacher_navigator_output + from scripts.generate_finetune_data import build_sft_row + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + from scripts.generate_finetune_data import score_candidate + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + index = _first_index_for_failure_class(failure_class) + spec = generate_case_spec(index, cards_by_id, dataset_version="figment_sft_v12_delta") + prepared = prepare_case(spec, cards_by_id) + candidate = assemble_teacher_navigator_output( + prepared, + { + "facts": [ + str(prepared.spec.structured_intake.get("chief_concern") or "field concern"), + str(prepared.spec.structured_intake.get("vitals") or "vitals pending"), + ], + "missing": prepared.expected_missing_observations, + "observe": prepared.expected_missing_observations, + "checklist": ["cite source cards", "collect required observations", "prepare grounded handoff"], + "uncertain": ["incomplete observations require local protocol review"], + "sbar": { + "situation": str(prepared.spec.structured_intake.get("chief_concern") or "field concern"), + "background": str(prepared.spec.structured_intake.get("setting") or "field intake"), + "assessment_observations_only": "deterministic red flags and cited observations only", + "handoff_request": "request protocol review per cited source cards", + }, + "script": "I am checking cited protocol observations.", + }, + ) + result = score_candidate(candidate, prepared) + assert result.passed is True, result.reward_components + assert not result.patched_fields + row = build_sft_row( + prepared=prepared, + result=result, + teacher_model_id="teacher-test", + candidate_total=1, + candidate_passed=1, + ) + return row, case_spec_record(prepared), result + + +def test_v12_failure_cycle_mixes_targeted_fix_and_replay_rows(): + from scripts.generate_finetune_data import V12_NAVIGATOR_COUNTS + from scripts.generate_finetune_data import _failure_class_for_index + + categories = Counter( + _failure_class_for_index(index, dataset_version="figment_sft_v12_delta") + for index in range(sum(V12_NAVIGATOR_COUNTS.values())) + ) + + assert categories == V12_NAVIGATOR_COUNTS + assert set(categories) == { + "postpartum_fever_required_obs_dual_card_selected_ids_visible_fields", + "postpartum_fever_required_obs_candidate_and_source_closure", + "wound_source_card_schema_replay", + "referral_candidate_pathway_replay", + } + + +def test_v12_postpartum_row_front_loads_preg_and_fever_cues_without_scaffold_fill(): + row, spec_record, result = _accepted_v12_row( + "postpartum_fever_required_obs_dual_card_selected_ids_visible_fields" + ) + output = json.loads(row["messages"][1]["content"]) + selected_ids = set(output["selected_required_observation_ids"]) + + assert row["version"] == "figment_sft_v12_delta" + assert spec_record["dataset_version"] == "figment_sft_v12_delta" + assert "PREG-DANGER-SIGNS-v1" in output["source_cards"] + assert "FEVER-RED-FLAGS-v1" in output["source_cards"] + assert [item["card_id"] for item in output["candidate_protocol_pathways"]] == [ + "FEVER-RED-FLAGS-v1", + "PREG-DANGER-SIGNS-v1", + ] + assert any(item.startswith("FEVER-RED-FLAGS-v1::required_observation::") for item in selected_ids) + assert any(item.startswith("PREG-DANGER-SIGNS-v1::required_observation::") for item in selected_ids) + assert not result.filled_required_observation_ids + + for field in ("missing_info_to_collect", "next_observations_to_collect"): + observation_text = json.dumps(output[field]).lower() + for cue in ( + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + ): + assert cue in observation_text + + +def test_v12_wound_replay_preserves_schema_source_cards_and_grounding(): + row, spec_record, result = _accepted_v12_row("wound_source_card_schema_replay") + output = json.loads(row["messages"][1]["content"]) + output_text = json.dumps(output).lower() + + assert spec_record["target_protocol_card_id"] == "WOUND-INFECTION-ESCALATION-v1" + assert {"WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"} <= set( + output["source_cards"] + ) + assert [item["card_id"] for item in output["candidate_protocol_pathways"]] == [ + "WOUND-INFECTION-ESCALATION-v1" + ] + assert any( + item.startswith("WOUND-INFECTION-ESCALATION-v1::required_observation::") + for item in output["selected_required_observation_ids"] + ) + assert "pregnan" not in output_text + assert not result.filled_required_observation_ids + + +def test_v12_referral_replay_keeps_target_and_fired_clinical_candidate_paths(): + row, spec_record, result = _accepted_v12_row("referral_candidate_pathway_replay") + output = json.loads(row["messages"][1]["content"]) + candidate_ids = [item["card_id"] for item in output["candidate_protocol_pathways"]] + + assert spec_record["target_protocol_card_id"] == "REFERRAL-SBAR-v1" + assert candidate_ids == ["REFERRAL-SBAR-v1", "PREG-DANGER-SIGNS-v1", "FEVER-RED-FLAGS-v1"] + assert {"REFERRAL-SBAR-v1", "SAFETY-BOUNDARIES-v1", "PREG-DANGER-SIGNS-v1", "FEVER-RED-FLAGS-v1"} <= set( + output["source_cards"] + ) + assert not result.filled_required_observation_ids + + +def test_v12_full_corpus_wrapper_pins_delta_defaults(): + from scripts.generate_v12_full_corpus import DEFAULT_NAVIGATOR_COUNT + from scripts.generate_v12_full_corpus import DEFAULT_OUTPUT_VERSION + from scripts.generate_v12_full_corpus import DEFAULT_REPAIR_COUNT + from scripts.generate_v12_full_corpus import DEFAULT_TEACHER_MODEL_ID + from scripts.generate_v12_full_corpus import build_corpus_args + from scripts.merge_v12_training_corpus import build_merge_args + + assert DEFAULT_OUTPUT_VERSION == "figment_sft_v12_delta" + assert DEFAULT_TEACHER_MODEL_ID == "nvidia/nemotron-3-ultra-550b-a55b:free" + assert DEFAULT_NAVIGATOR_COUNT == 560 + assert DEFAULT_REPAIR_COUNT == 0 + args = build_corpus_args(["--navigator-count", "8", "--repair-count", "0", "--dry-run"]) + assert args[args.index("--navigator-count") + 1] == "8" + assert args[args.index("--repair-count") + 1] == "0" + assert args[-1] == "--dry-run" + + merge_args = build_merge_args(["--skip-verify"]) + assert merge_args[merge_args.index("--dataset-version") + 1] == "figment_sft_v12" + assert merge_args[merge_args.index("--base") + 1] == "data/finetune/figment_sft_v10.jsonl" + assert "--skip-verify" in merge_args diff --git a/tests/test_finetune_v13_data_plan.py b/tests/test_finetune_v13_data_plan.py new file mode 100644 index 0000000000000000000000000000000000000000..f5eca4d599b3139a210d67badfebbbd3c28b1519 --- /dev/null +++ b/tests/test_finetune_v13_data_plan.py @@ -0,0 +1,171 @@ +import json +from collections import Counter + + +def _first_index_for_failure_class(failure_class: str) -> int: + from scripts.generate_finetune_data import V13_NAVIGATOR_COUNTS + from scripts.generate_finetune_data import _failure_class_for_index + + for index in range(sum(V13_NAVIGATOR_COUNTS.values())): + if _failure_class_for_index(index, dataset_version="figment_sft_v13_delta") == failure_class: + return index + raise AssertionError(f"missing v13 failure class: {failure_class}") + + +def _accepted_v13_row(failure_class: str): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import assemble_teacher_navigator_output + from scripts.generate_finetune_data import build_sft_row + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + from scripts.generate_finetune_data import score_candidate + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + index = _first_index_for_failure_class(failure_class) + spec = generate_case_spec(index, cards_by_id, dataset_version="figment_sft_v13_delta") + prepared = prepare_case(spec, cards_by_id) + candidate = assemble_teacher_navigator_output( + prepared, + { + "facts": [ + str(prepared.spec.structured_intake.get("chief_concern") or "field concern"), + str(prepared.spec.structured_intake.get("vitals") or "vitals pending"), + ], + "missing": prepared.expected_missing_observations, + "observe": prepared.expected_missing_observations, + "checklist": ["cite source cards", "collect required observations", "prepare grounded handoff"], + "uncertain": ["incomplete observations require local protocol review"], + "sbar": { + "situation": str(prepared.spec.structured_intake.get("chief_concern") or "field concern"), + "background": str(prepared.spec.structured_intake.get("setting") or "field intake"), + "assessment_observations_only": "deterministic red flags and cited observations only", + "handoff_request": "request protocol review per cited source cards", + }, + "script": "I am checking cited protocol observations.", + }, + ) + result = score_candidate(candidate, prepared) + assert result.passed is True, result.reward_components + assert not result.patched_fields + row = build_sft_row( + prepared=prepared, + result=result, + teacher_model_id="teacher-test", + candidate_total=1, + candidate_passed=1, + ) + return row, case_spec_record(prepared), result + + +def test_v13_failure_cycle_targets_v12_gap_with_replay_rows(): + from scripts.generate_finetune_data import V13_NAVIGATOR_COUNTS + from scripts.generate_finetune_data import _failure_class_for_index + + categories = Counter( + _failure_class_for_index(index, dataset_version="figment_sft_v13_delta") + for index in range(sum(V13_NAVIGATOR_COUNTS.values())) + ) + + assert categories == V13_NAVIGATOR_COUNTS + assert set(categories) == { + "postpartum_fever_required_obs_visible_preg_source_card_cue_closure", + "postpartum_fever_required_obs_visible_preg_candidate_pathway_closure", + "postpartum_fever_required_obs_selected_id_compressed_field_repair", + "wound_source_card_schema_replay", + "referral_candidate_pathway_replay", + } + + +def test_v13_postpartum_rows_make_preg_cues_visible_not_only_selected_ids(): + for failure_class in ( + "postpartum_fever_required_obs_visible_preg_source_card_cue_closure", + "postpartum_fever_required_obs_visible_preg_candidate_pathway_closure", + "postpartum_fever_required_obs_selected_id_compressed_field_repair", + ): + row, spec_record, result = _accepted_v13_row(failure_class) + output = json.loads(row["messages"][1]["content"]) + selected_ids = set(output["selected_required_observation_ids"]) + + assert row["version"] == "figment_sft_v13_delta" + assert spec_record["dataset_version"] == "figment_sft_v13_delta" + assert "PREG-DANGER-SIGNS-v1" in output["source_cards"] + assert "FEVER-RED-FLAGS-v1" in output["source_cards"] + assert [item["card_id"] for item in output["candidate_protocol_pathways"]] == [ + "FEVER-RED-FLAGS-v1", + "PREG-DANGER-SIGNS-v1", + ] + assert any(item.startswith("FEVER-RED-FLAGS-v1::required_observation::") for item in selected_ids) + assert any(item.startswith("PREG-DANGER-SIGNS-v1::required_observation::") for item in selected_ids) + assert not result.filled_required_observation_ids + + for field in ("missing_info_to_collect", "next_observations_to_collect"): + observation_text = json.dumps(output[field]).lower() + for cue in ( + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + ): + assert cue in observation_text + + +def test_v13_replay_rows_are_version_tagged_and_preserve_guardrails(): + wound_row, wound_spec, wound_result = _accepted_v13_row("wound_source_card_schema_replay") + wound_output = json.loads(wound_row["messages"][1]["content"]) + wound_text = json.dumps(wound_output).lower() + + assert "v13" in wound_spec["tags"] + assert wound_spec["target_protocol_card_id"] == "WOUND-INFECTION-ESCALATION-v1" + assert {"WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"} <= set( + wound_output["source_cards"] + ) + assert [item["card_id"] for item in wound_output["candidate_protocol_pathways"]] == [ + "WOUND-INFECTION-ESCALATION-v1" + ] + assert "pregnan" not in wound_text + assert not wound_result.filled_required_observation_ids + + referral_row, referral_spec, referral_result = _accepted_v13_row("referral_candidate_pathway_replay") + referral_output = json.loads(referral_row["messages"][1]["content"]) + assert "v13" in referral_spec["tags"] + assert referral_spec["target_protocol_card_id"] == "REFERRAL-SBAR-v1" + assert [item["card_id"] for item in referral_output["candidate_protocol_pathways"]] == [ + "REFERRAL-SBAR-v1", + "PREG-DANGER-SIGNS-v1", + "FEVER-RED-FLAGS-v1", + ] + assert not referral_result.filled_required_observation_ids + + +def test_v13_full_corpus_wrapper_pins_delta_defaults(): + from scripts.generate_v13_full_corpus import DEFAULT_NAVIGATOR_COUNT + from scripts.generate_v13_full_corpus import DEFAULT_OUTPUT_VERSION + from scripts.generate_v13_full_corpus import DEFAULT_REPAIR_COUNT + from scripts.generate_v13_full_corpus import DEFAULT_TEACHER_MODEL_ID + from scripts.generate_v13_full_corpus import build_corpus_args + from scripts.merge_v13_training_corpus import build_merge_args + + assert DEFAULT_OUTPUT_VERSION == "figment_sft_v13_delta" + assert DEFAULT_TEACHER_MODEL_ID == "nvidia/nemotron-3-ultra-550b-a55b" + assert DEFAULT_NAVIGATOR_COUNT == 1000 + assert DEFAULT_REPAIR_COUNT == 0 + args = build_corpus_args(["--navigator-count", "8", "--repair-count", "0", "--dry-run"]) + assert args[args.index("--navigator-count") + 1] == "8" + assert args[args.index("--repair-count") + 1] == "0" + assert "--no-teacher-worker" in args + assert args[-1] == "--dry-run" + + merge_args = build_merge_args(["--skip-verify"]) + assert merge_args[merge_args.index("--dataset-version") + 1] == "figment_sft_v13" + assert merge_args[merge_args.index("--base") + 1] == "data/finetune/figment_sft_v10.jsonl" + assert "--skip-verify" in merge_args diff --git a/tests/test_finetune_v14_data_plan.py b/tests/test_finetune_v14_data_plan.py new file mode 100644 index 0000000000000000000000000000000000000000..5967093deb627718c68e174c001f3bca5dfcde19 --- /dev/null +++ b/tests/test_finetune_v14_data_plan.py @@ -0,0 +1,157 @@ +import json +from collections import Counter + + +def _first_index_for_failure_class(failure_class: str) -> int: + from scripts.generate_finetune_data import V14_NAVIGATOR_COUNTS + from scripts.generate_finetune_data import _failure_class_for_index + + for index in range(sum(V14_NAVIGATOR_COUNTS.values())): + if _failure_class_for_index(index, dataset_version="figment_sft_v14_delta") == failure_class: + return index + raise AssertionError(f"missing v14 failure class: {failure_class}") + + +def _accepted_v14_row(failure_class: str): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import assemble_teacher_navigator_output + from scripts.generate_finetune_data import build_sft_row + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + from scripts.generate_finetune_data import score_candidate + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + index = _first_index_for_failure_class(failure_class) + spec = generate_case_spec(index, cards_by_id, dataset_version="figment_sft_v14_delta") + prepared = prepare_case(spec, cards_by_id) + candidate = assemble_teacher_navigator_output( + prepared, + { + "facts": [ + str(prepared.spec.structured_intake.get("chief_concern") or "field concern"), + str(prepared.spec.structured_intake.get("vitals") or "vitals pending"), + ], + "missing": prepared.expected_missing_observations, + "observe": prepared.expected_missing_observations, + "checklist": ["cite source cards", "collect required observations", "prepare grounded handoff"], + "uncertain": ["incomplete observations require local protocol review"], + "sbar": { + "situation": str(prepared.spec.structured_intake.get("chief_concern") or "field concern"), + "background": str(prepared.spec.structured_intake.get("setting") or "field intake"), + "assessment_observations_only": "deterministic red flags and cited observations only", + "handoff_request": "request protocol review per cited source cards", + }, + "script": "I am checking cited protocol observations.", + }, + ) + result = score_candidate(candidate, prepared) + assert result.passed is True, result.reward_components + assert not result.patched_fields + row = build_sft_row( + prepared=prepared, + result=result, + teacher_model_id="teacher-test", + candidate_total=1, + candidate_passed=1, + ) + return row, case_spec_record(prepared), result + + +def test_v14_failure_cycle_expands_v13_delta_with_wound_replay_boost(): + from scripts.generate_finetune_data import V14_NAVIGATOR_COUNTS + from scripts.generate_finetune_data import _failure_class_for_index + + categories = Counter( + _failure_class_for_index(index, dataset_version="figment_sft_v14_delta") + for index in range(sum(V14_NAVIGATOR_COUNTS.values())) + ) + + assert categories == V14_NAVIGATOR_COUNTS + assert categories["wound_source_card_schema_replay"] == 200 + assert sum(categories.values()) == 1120 + + +def test_v14_postpartum_rows_make_preg_cues_visible_without_scaffold_fill(): + for failure_class in ( + "postpartum_fever_required_obs_visible_preg_source_card_cue_closure", + "postpartum_fever_required_obs_visible_preg_candidate_pathway_closure", + "postpartum_fever_required_obs_selected_id_compressed_field_repair", + ): + row, spec_record, result = _accepted_v14_row(failure_class) + output = json.loads(row["messages"][1]["content"]) + selected_ids = set(output["selected_required_observation_ids"]) + + assert row["version"] == "figment_sft_v14_delta" + assert spec_record["dataset_version"] == "figment_sft_v14_delta" + assert "v14" in spec_record["tags"] + assert "PREG-DANGER-SIGNS-v1" in output["source_cards"] + assert "FEVER-RED-FLAGS-v1" in output["source_cards"] + assert [item["card_id"] for item in output["candidate_protocol_pathways"]] == [ + "FEVER-RED-FLAGS-v1", + "PREG-DANGER-SIGNS-v1", + ] + assert any(item.startswith("FEVER-RED-FLAGS-v1::required_observation::") for item in selected_ids) + assert any(item.startswith("PREG-DANGER-SIGNS-v1::required_observation::") for item in selected_ids) + assert not result.filled_required_observation_ids + + observation_text = json.dumps( + output["missing_info_to_collect"] + output["next_observations_to_collect"] + ).lower() + for cue in ( + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + "temperature if available", + "age or pregnancy status", + "mental status", + "neck stiffness report", + "rash report", + "hydration observations", + "available vital signs", + ): + assert cue in observation_text + + +def test_v14_wound_replay_preserves_source_cards_schema_and_no_pregnancy_bleedthrough(): + row, spec_record, result = _accepted_v14_row("wound_source_card_schema_replay") + output = json.loads(row["messages"][1]["content"]) + output_text = json.dumps(output).lower() + + assert "v14" in spec_record["tags"] + assert spec_record["target_protocol_card_id"] == "WOUND-INFECTION-ESCALATION-v1" + assert {"WOUND-INFECTION-ESCALATION-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"} <= set( + output["source_cards"] + ) + assert [item["card_id"] for item in output["candidate_protocol_pathways"]] == [ + "WOUND-INFECTION-ESCALATION-v1" + ] + assert "pregnan" not in output_text + assert not result.filled_required_observation_ids + + +def test_v14_full_corpus_wrapper_pins_delta_defaults(): + from scripts.generate_v14_full_corpus import DEFAULT_NAVIGATOR_COUNT + from scripts.generate_v14_full_corpus import DEFAULT_OUTPUT_VERSION + from scripts.generate_v14_full_corpus import DEFAULT_REPAIR_COUNT + from scripts.generate_v14_full_corpus import DEFAULT_TEACHER_MODEL_ID + from scripts.generate_v14_full_corpus import build_corpus_args + from scripts.merge_v14_training_corpus import build_merge_args + + assert DEFAULT_OUTPUT_VERSION == "figment_sft_v14_delta" + assert DEFAULT_TEACHER_MODEL_ID == "nvidia/nemotron-3-ultra-550b-a55b" + assert DEFAULT_NAVIGATOR_COUNT == 1120 + assert DEFAULT_REPAIR_COUNT == 0 + args = build_corpus_args(["--navigator-count", "8", "--repair-count", "0", "--dry-run"]) + assert args[args.index("--navigator-count") + 1] == "8" + assert args[args.index("--repair-count") + 1] == "0" + assert "--no-teacher-worker" in args + assert args[-1] == "--dry-run" + + merge_args = build_merge_args(["--skip-verify"]) + assert merge_args[merge_args.index("--dataset-version") + 1] == "figment_sft_v14" + assert merge_args[merge_args.index("--base") + 1] == "data/finetune/figment_sft_v10.jsonl" + assert "--skip-verify" in merge_args diff --git a/tests/test_finetune_v2_data_plan.py b/tests/test_finetune_v2_data_plan.py new file mode 100644 index 0000000000000000000000000000000000000000..25eb757d5f7a18d511e39096875e8ea79068bf6b --- /dev/null +++ b/tests/test_finetune_v2_data_plan.py @@ -0,0 +1,638 @@ +import json +import argparse +from collections import Counter +from pathlib import Path + +import pytest + + +def test_dataset_paths_are_versioned(): + from scripts.generate_finetune_data import dataset_paths + + paths = dataset_paths("figment_sft_v2") + + assert paths["output"] == Path("data/finetune/figment_sft_v2.jsonl") + assert paths["manifest"] == Path("data/finetune/figment_sft_v2_manifest.json") + assert paths["case_specs"] == Path("data/finetune/figment_sft_v2_case_specs.jsonl") + + +def test_repair_augmentation_paths_are_versioned(): + from scripts.augment_finetune_repair_rows import dataset_paths + + paths = dataset_paths("figment_sft_v2") + + assert paths["dataset"] == Path("data/finetune/figment_sft_v2.jsonl") + assert paths["manifest"] == Path("data/finetune/figment_sft_v2_manifest.json") + assert paths["case_specs"] == Path("data/finetune/figment_sft_v2_case_specs.jsonl") + + +def test_v2_case_ids_and_rows_use_requested_dataset_version(): + from scripts.generate_finetune_data import build_sft_row + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + from scripts.generate_finetune_data import score_candidate + from figment.retrieval import load_protocol_cards + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(0, cards_by_id, dataset_version="figment_sft_v2") + prepared = prepare_case(spec, cards_by_id) + result = score_candidate({}, prepared) + row = build_sft_row( + prepared=prepared, + result=result, + teacher_model_id="teacher-test", + candidate_total=1, + candidate_passed=1, + ) + + assert spec.case_id.startswith("figment_sft_v2-") + assert row["version"] == "figment_sft_v2" + assert row["case_id"].startswith("figment_sft_v2-") + assert case_spec_record(prepared)["dataset_version"] == "figment_sft_v2" + + +def test_shard_case_indices_are_disjoint(): + from scripts.generate_finetune_data import case_index_for_attempt + + shard_0 = [case_index_for_attempt(attempt, start_index=0, index_stride=4) for attempt in range(5)] + shard_1 = [case_index_for_attempt(attempt, start_index=1, index_stride=4) for attempt in range(5)] + + assert shard_0 == [0, 4, 8, 12, 16] + assert shard_1 == [1, 5, 9, 13, 17] + assert set(shard_0).isdisjoint(shard_1) + + +def test_v3_full_corpus_shards_partition_requested_rows(): + from scripts.generate_v3_full_corpus import build_shard_specs + + specs = build_shard_specs( + navigator_count=105, + rows_per_shard=50, + base_start_index=20000, + shard_prefix=Path("data/finetune/shards/figment_sft_v3_full_shard"), + ) + + assert [spec.row_count for spec in specs] == [50, 50, 5] + assert [spec.start_index for spec in specs] == [20000, 20001, 20002] + assert [spec.index_stride for spec in specs] == [3, 3, 3] + assert [spec.output.name for spec in specs] == [ + "figment_sft_v3_full_shard0.jsonl", + "figment_sft_v3_full_shard1.jsonl", + "figment_sft_v3_full_shard2.jsonl", + ] + + +def test_v3_full_corpus_repair_command_uses_explicit_paths(): + from scripts.generate_v3_full_corpus import build_repair_command + + args = argparse.Namespace( + dataset_version="figment_sft_v3", + output=Path("tmp/custom.jsonl"), + case_specs=Path("tmp/custom_case_specs.jsonl"), + manifest=Path("tmp/custom_manifest.json"), + repair_count=12, + ) + + cmd = build_repair_command(args) + + assert "--dataset" in cmd + assert cmd[cmd.index("--dataset") + 1] == "tmp/custom.jsonl" + assert cmd[cmd.index("--case-specs") + 1] == "tmp/custom_case_specs.jsonl" + assert cmd[cmd.index("--manifest") + 1] == "tmp/custom_manifest.json" + assert cmd[cmd.index("--repair-count") + 1] == "12" + + +def test_v2_failure_distribution_matches_training_plan(): + from scripts.generate_finetune_data import _failure_class_for_index + + categories = [_failure_class_for_index(index, dataset_version="figment_sft_v2") for index in range(100)] + + assert categories.count("missing_observation_cues") == 40 + assert categories.count("negation_safety_boundary") == 25 + assert categories.count("source_card_candidate_pathway") == 20 + assert categories.count("sbar_grounding") == 10 + assert categories.count("forbidden_instruction_avoidance") == 3 + assert categories.count("fallback_rescue_shape") == 2 + + +def test_v3_failure_distribution_matches_field_workflow_plan(): + from scripts.generate_finetune_data import _failure_class_for_index + + categories = [_failure_class_for_index(index, dataset_version="figment_sft_v3") for index in range(100)] + + assert categories.count("rural_clinic_intake") == 18 + assert categories.count("disaster_triage") == 16 + assert categories.count("radio_handoff") == 8 + assert categories.count("asr_confirmed_text") == 6 + assert categories.count("escalation_precision") == 14 + assert categories.count("missing_observation_prioritization") == 14 + assert categories.count("sbar_handoff_usefulness") == 10 + assert categories.count("source_card_discipline") == 6 + assert categories.count("low_resource_constraints") == 7 + assert categories.count("workflow_repair_seed") == 1 + + +def test_v4_failure_distribution_targets_handoff_gaps(): + from scripts.generate_finetune_data import _failure_class_for_index + + categories = [_failure_class_for_index(index, dataset_version="figment_sft_v4") for index in range(100)] + + assert categories.count("radio_handoff") == 25 + assert categories.count("sbar_handoff_usefulness") == 22 + assert categories.count("source_card_discipline") == 14 + assert categories.count("low_resource_constraints") == 10 + assert categories.count("missing_observation_prioritization") == 10 + assert categories.count("workflow_repair_seed") == 7 + assert categories.count("rural_clinic_intake") == 4 + assert categories.count("disaster_triage") == 3 + assert categories.count("escalation_precision") == 5 + + +def test_v3_case_specs_include_field_workflow_metadata_and_safe_boundaries(): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import forbidden_behavior_for_version + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(0, cards_by_id, dataset_version="figment_sft_v3") + prepared = prepare_case(spec, cards_by_id) + record = case_spec_record(prepared) + + assert spec.failure_class == "rural_clinic_intake" + assert spec.structured_intake["workflow_category"] == "rural_clinic_intake" + assert "field_workflow" in spec.tags + assert "rural_clinic" in spec.tags + assert record["workflow_category"] == "rural_clinic_intake" + assert record["workflow_priority_observations"] == prepared.expected_missing_observations[:5] + assert record["field_workflow_holdout_relevant"] is True + assert 1 <= len(prepared.expected_missing_observations) <= 8 + assert spec.structured_intake["workflow_constraint"] + assert "medication" not in json.dumps(forbidden_behavior_for_version("figment_sft_v3")).lower() + + +def test_v4_case_specs_use_field_workflow_policy_and_handoff_focus(): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import forbidden_behavior_for_version + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(0, cards_by_id, dataset_version="figment_sft_v4") + prepared = prepare_case(spec, cards_by_id) + record = case_spec_record(prepared) + + assert spec.failure_class == "radio_handoff" + assert spec.target_protocol_card_id == "REFERRAL-SBAR-v1" + assert spec.structured_intake["workflow_category"] == "radio_handoff" + assert "V4 field-workflow category" in spec.structured_intake["responder_note"] + assert "V3 field-workflow category" not in spec.structured_intake["responder_note"] + assert "field_workflow" in spec.tags + assert "sbar" in spec.tags + assert record["dataset_version"] == "figment_sft_v4" + assert "medication" not in json.dumps(forbidden_behavior_for_version("figment_sft_v4")).lower() + + +def test_v4_escalation_precision_cases_are_hard_negative_safety_rows(): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import generate_case_spec + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(95, cards_by_id, dataset_version="figment_sft_v4") + + assert spec.failure_class == "escalation_precision" + assert spec.target_protocol_card_id == "SAFETY-BOUNDARIES-v1" + assert spec.high_risk is True + assert spec.structured_intake["workflow_category"] == "escalation_precision" + + +def test_v3_exclusion_rejects_exact_or_near_eval_neighbors(): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import ExclusionSignature + from scripts.generate_finetune_data import _clinical_intake_hash + from scripts.generate_finetune_data import _clinical_intake_tokens + from scripts.generate_finetune_data import _eval_exclusion_neighbor + from scripts.generate_finetune_data import generate_case_spec + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(200, cards_by_id, dataset_version="figment_sft_v3") + signature = ExclusionSignature( + case_id="holdout-near", + source_path="data/eval/field_workflow_holdout_v1.jsonl", + target_protocol_card_id=spec.target_protocol_card_id, + workflow_category=spec.structured_intake["workflow_category"], + clinical_hash=_clinical_intake_hash(spec.structured_intake), + tokens=frozenset(_clinical_intake_tokens(spec.structured_intake)), + ) + + match = _eval_exclusion_neighbor(spec, [signature]) + + assert match is not None + assert match["reason"] == "eval_exclusion_exact_clinical_neighbor" + + +def test_v2_repair_scope_schedule_matches_training_plan(): + from scripts.augment_finetune_repair_rows import _scope_schedule + + counts = Counter(_scope_schedule(400, dataset_version="figment_sft_v2")) + + assert counts == { + "handoff_note_sbar": 100, + "missing_observations": 100, + "citations_and_pathways": 75, + "forbidden_clinical_language": 50, + "schema": 50, + "protocol_urgency": 25, + } + + +def test_v3_repair_scope_schedule_matches_field_workflow_plan(): + from scripts.augment_finetune_repair_rows import _scope_schedule + + counts = Counter(_scope_schedule(500, dataset_version="figment_sft_v3")) + + assert counts == { + "handoff_note_sbar": 120, + "missing_observations": 110, + "citations_and_pathways": 90, + "forbidden_clinical_language": 60, + "protocol_urgency": 60, + "schema": 60, + } + + +def test_v4_repair_scope_schedule_targets_handoff_and_citations(): + from scripts.augment_finetune_repair_rows import _scope_schedule + + counts = Counter(_scope_schedule(100, dataset_version="figment_sft_v4")) + + assert counts == { + "handoff_note_sbar": 45, + "citations_and_pathways": 25, + "missing_observations": 15, + "forbidden_clinical_language": 5, + "protocol_urgency": 5, + "schema": 5, + } + + +def test_v4_full_corpus_wrapper_pins_v4_defaults(): + from scripts.generate_v4_full_corpus import DEFAULT_ARGS + from scripts.generate_v4_full_corpus import build_corpus_args + + assert DEFAULT_ARGS[DEFAULT_ARGS.index("--dataset-version") + 1] == "figment_sft_v4" + assert DEFAULT_ARGS[DEFAULT_ARGS.index("--navigator-count") + 1] == "1500" + assert DEFAULT_ARGS[DEFAULT_ARGS.index("--repair-count") + 1] == "150" + assert DEFAULT_ARGS[DEFAULT_ARGS.index("--output") + 1] == "data/finetune/figment_sft_v4.jsonl" + assert DEFAULT_ARGS[DEFAULT_ARGS.index("--modal-output-dir") + 1] == "data/finetune/modal/figment_sft_v4" + args = build_corpus_args(["--navigator-count", "2", "--output", "tmp/smoke.jsonl"]) + assert args[-4:] == ["--navigator-count", "2", "--output", "tmp/smoke.jsonl"] + + +def test_merge_finetune_shards_writes_sorted_rows_and_manifest(tmp_path): + from scripts.merge_finetune_shards import merge_shards + + prefix = tmp_path / "figment_sft_v2_shard" + shard_0 = prefix.with_name(f"{prefix.name}0.jsonl") + shard_1 = prefix.with_name(f"{prefix.name}1.jsonl") + specs_0 = prefix.with_name(f"{prefix.name}0_case_specs.jsonl") + specs_1 = prefix.with_name(f"{prefix.name}1_case_specs.jsonl") + manifest_0 = prefix.with_name(f"{prefix.name}0_manifest.json") + manifest_1 = prefix.with_name(f"{prefix.name}1_manifest.json") + shard_0.write_text( + json.dumps({"case_id": "figment_sft_v2-000004", "version": "figment_sft_v2", "category": "missing"}) + "\n", + encoding="utf-8", + ) + shard_1.write_text( + json.dumps({"case_id": "figment_sft_v2-000001", "version": "figment_sft_v2", "category": "negation"}) + "\n", + encoding="utf-8", + ) + specs_0.write_text( + json.dumps({"case_id": "figment_sft_v2-000004", "dataset_version": "figment_sft_v2"}) + "\n", + encoding="utf-8", + ) + specs_1.write_text( + json.dumps({"case_id": "figment_sft_v2-000001", "dataset_version": "figment_sft_v2"}) + "\n", + encoding="utf-8", + ) + manifest_0.write_text(json.dumps({"attempts": 2}) + "\n", encoding="utf-8") + manifest_1.write_text(json.dumps({"attempts": 3}) + "\n", encoding="utf-8") + + output = tmp_path / "merged.jsonl" + case_specs = tmp_path / "merged_specs.jsonl" + manifest = tmp_path / "merged_manifest.json" + summary = merge_shards( + dataset_version="figment_sft_v2", + shard_prefix=prefix, + shard_count=2, + output_path=output, + case_specs_path=case_specs, + manifest_path=manifest, + ) + + merged_ids = [json.loads(line)["case_id"] for line in output.read_text(encoding="utf-8").splitlines()] + + assert merged_ids == ["figment_sft_v2-000001", "figment_sft_v2-000004"] + assert summary["row_count"] == 2 + assert summary["case_spec_count"] == 2 + assert summary["shard_count"] == 2 + assert json.loads(manifest.read_text(encoding="utf-8"))["source_attempts"] == 5 + + +def test_v2_forbidden_lexical_gate_rejects_safe_sounding_tripwires(): + from scripts.generate_finetune_data import v2_policy_issues + + output = { + "do_not_do": [ + "Do not diagnose.", + "Do not prescribe, dose, administer, or start medication.", + ], + "responder_checklist": ["Use protocol cards."], + } + + issues = v2_policy_issues( + output, + failure_class="missing_observation_cues", + expected_red_flag_rule_ids=["AMS-001"], + expected_candidate_pathway_card_ids=["AMS-RED-FLAGS-v1"], + ) + + assert "forbidden_lexical_tripwire:medication" in issues + assert "forbidden_lexical_tripwire:prescribe" in issues + assert "forbidden_lexical_tripwire:dose" in issues + + +def test_v3_policy_rejects_generic_and_low_resource_mismatch(): + from scripts.generate_finetune_data import v3_policy_issues + + output = { + "missing_info_to_collect": ["repeat vitals", "monitor closely", "follow protocol"], + "next_observations_to_collect": ["repeat vitals", "assess patient", "collect more information"], + "responder_checklist": ["monitor closely", "follow protocol", "repeat vitals"], + "handoff_note_sbar": { + "situation": "", + "background": "", + "assessment_observations_only": "", + "handoff_request": "", + }, + } + + issues = v3_policy_issues( + output, + failure_class="low_resource_constraints", + expected_red_flag_rule_ids=[], + expected_candidate_pathway_card_ids=["RESP-DISTRESS-RED-FLAGS-v1"], + structured_intake={ + "available_supplies": "no pulse oximeter, no BP cuff, intermittent radio only", + "responder_note": "Synthetic field-workflow case.", + }, + ) + + assert "generic_output_dominated" in issues + assert "low_resource_unavailable_pulse_ox_requested" in issues + assert "handoff_sbar_missing_required_parts" in issues + + +def test_generate_field_workflow_holdout_writes_eval_rows_and_manifest(tmp_path): + from scripts.generate_field_workflow_holdout import generate_holdout + + output = tmp_path / "field_workflow_holdout_v1.jsonl" + manifest = tmp_path / "field_workflow_holdout_v1_manifest.json" + + summary = generate_holdout(count=12, output_path=output, manifest_path=manifest) + rows = [json.loads(line) for line in output.read_text(encoding="utf-8").splitlines()] + manifest_json = json.loads(manifest.read_text(encoding="utf-8")) + + assert summary["row_count"] == 12 + assert len(rows) == 12 + assert all(row["case_id"].startswith("field_workflow_holdout_v1-") for row in rows) + assert all(row["dataset_version"] == "field_workflow_holdout_v1" for row in rows) + assert all(row["workflow_category"] for row in rows) + assert all("messages" not in row for row in rows) + assert manifest_json["row_count"] == 12 + assert manifest_json["holdout_policy"]["never_train_on_this_file"] is True + assert manifest_json["output_sha256"] + + +def test_teacher_backend_retry_detector_handles_rate_limits(): + from figment.model_client import ModelClientError + from scripts.generate_finetune_data import _is_retryable_teacher_error + + error = ModelClientError("teacher failed; http_status=429; reason=Too Many Requests") + + assert _is_retryable_teacher_error(error) is True + + +def test_openrouter_teacher_metadata_env_names(monkeypatch): + from scripts.generate_finetune_data import _api_key_env_name + from scripts.generate_finetune_data import _endpoint_env_name + + model_id = "nvidia/nemotron-3-ultra-550b-a55b:free" + monkeypatch.setenv("OPENROUTER_BASE_URL", "https://openrouter.ai/api/v1") + monkeypatch.setenv("OPENROUTER_API_KEY", "test-key") + monkeypatch.setenv("OPENROUTER_FREE_MODEL_ID", model_id) + + assert _endpoint_env_name(model_id) == "OPENROUTER_BASE_URL" + assert _api_key_env_name(model_id) == "OPENROUTER_API_KEY" + + +def test_openrouter_teacher_uses_non_streaming_path(monkeypatch): + from scripts import generate_finetune_data as generator + + client = generator.TeacherClient( + endpoint="https://openrouter.ai/api/v1", + model_id="nvidia/nemotron-3-ultra-550b-a55b:free", + auth_headers={}, + timeout_seconds=10, + max_tokens=64, + endpoint_env="OPENROUTER_BASE_URL", + api_key_env="OPENROUTER_API_KEY", + ) + + def fake_non_streaming(client_arg, prompt): + assert client_arg is client + assert prompt == "prompt" + return {"ok": True} + + def fake_streaming(client_arg, prompt): + raise AssertionError("OpenRouter teacher calls should not use the streaming SSE path") + + monkeypatch.setattr(generator, "_teacher_json_http_non_streaming", fake_non_streaming, raising=False) + monkeypatch.setattr(generator, "_stream_teacher_json_http", fake_streaming) + + assert generator._stream_teacher_json(client, "prompt") == {"ok": True} + + +def test_verify_v2_uses_scorer_safe_forbidden_behavior(): + from scripts.verify_finetune_harness_alignment import _forbidden_behavior_for_dataset_version + + forbidden_behavior = _forbidden_behavior_for_dataset_version("figment_sft_v2") + + assert "medication" not in json.dumps(forbidden_behavior).lower() + assert "downgrade" not in json.dumps(forbidden_behavior).lower() + + +def test_v2_negation_gate_rejects_red_flags_and_condition_targets(): + from scripts.generate_finetune_data import v2_policy_issues + + output = { + "protocol_urgency": "emergency", + "red_flags": [ + { + "card_id": "CHEST-PAIN-ESCALATION-v1", + "rule_id": "red_flag_chest_pain", + "urgency": "emergency", + } + ], + "candidate_protocol_pathways": [ + {"card_id": "CHEST-PAIN-ESCALATION-v1", "reason_relevant": "bad negation target"} + ], + "source_cards": ["CHEST-PAIN-ESCALATION-v1", "SAFETY-BOUNDARIES-v1"], + } + + issues = v2_policy_issues( + output, + failure_class="negation_safety_boundary", + expected_red_flag_rule_ids=[], + expected_candidate_pathway_card_ids=["SAFETY-BOUNDARIES-v1"], + ) + + assert "negation_red_flags_must_be_empty" in issues + assert "negation_candidate_pathway_must_be_safety_or_sbar" in issues + + +def test_verify_v2_rejects_dataset_forbidden_lexical_tripwires(tmp_path): + from scripts.verify_finetune_harness_alignment import verify_rows + + case_specs = tmp_path / "specs.jsonl" + dataset = tmp_path / "rows.jsonl" + spec = { + "case_id": "figment_sft_v2-000000", + "failure_class": "negation_safety_boundary", + "target_protocol_card_id": "SAFETY-BOUNDARIES-v1", + "structured_intake": { + "setting": "training triage station", + "patient_age": "29 years", + "pregnancy_status": "not_applicable", + "chief_concern": "routine cough check", + "symptoms": "mild cough, no fever, no shortness of breath, no chest pain", + "vitals": "temperature normal; pulse regular; respirations unlabored", + "allergies": "unknown", + "medications": "unknown", + "available_supplies": "radio and protocol binder", + "responder_note": "Synthetic v2 test case.", + "confirmed": True, + }, + "expected_red_flag_rule_ids": [], + "expected_min_protocol_urgency": "routine", + "expected_source_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], + "expected_candidate_pathway_card_ids": ["SAFETY-BOUNDARIES-v1"], + "expected_missing_observations": ["confirmed intake status"], + "retrieved_card_ids": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], + "tags": ["negation", "safety_boundary"], + } + output = { + "protocol_urgency": "routine", + "red_flags": [], + "intake_facts": [{"fact": "Mild cough only.", "status": "reported", "source": "structured_field"}], + "candidate_protocol_pathways": [ + {"card_id": "SAFETY-BOUNDARIES-v1", "reason_relevant": "Safety-boundary review."} + ], + "missing_info_to_collect": ["confirmed intake status"], + "next_observations_to_collect": ["confirmed intake status"], + "conflicts_or_uncertainties": ["Medication history unknown."], + "responder_checklist": ["Confirm intake."], + "do_not_do": ["Do not prescribe medication."], + "source_cards": ["SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], + "handoff_note_sbar": { + "situation": "Routine cough check.", + "background": "Training triage station.", + "assessment_observations_only": "Mild cough only.", + "handoff_request": "Protocol review requested.", + }, + "responder_plain_language_script": "Protocol review requested.", + "safety_boundary": "Prototype protocol navigation only.", + } + row = { + "case_id": spec["case_id"], + "uuid": spec["case_id"], + "version": "figment_sft_v2", + "category": "negation_safety_boundary", + "messages": [ + {"role": "user", "content": "will mismatch before lexical gate matters"}, + {"role": "assistant", "content": json.dumps(output, sort_keys=True)}, + ], + "metadata": { + "task_type": "navigator_full", + "failure_class": "negation_safety_boundary", + "prompt_hash": "x", + "prompt_template_hash": "y", + "teacher_label_mode": "streamed_ultra_semantic_notes_harness_prompt", + }, + } + case_specs.write_text(json.dumps(spec) + "\n", encoding="utf-8") + dataset.write_text(json.dumps(row) + "\n", encoding="utf-8") + + summary = verify_rows(dataset_path=dataset, case_specs_path=case_specs) + + assert summary["passed"] is False + assert summary["issue_types"]["v2_forbidden_lexical_tripwire"] >= 1 + + +def test_verify_v3_focused_repair_applies_policy_to_reconstructed_full_output(tmp_path): + from figment.retrieval import load_protocol_cards + from scripts.augment_finetune_repair_rows import build_repair_row + from scripts.generate_finetune_data import assemble_teacher_navigator_output + from scripts.generate_finetune_data import build_sft_row + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + from scripts.generate_finetune_data import score_candidate + from scripts.verify_finetune_harness_alignment import verify_rows + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(0, cards_by_id, dataset_version="figment_sft_v3") + prepared = prepare_case(spec, cards_by_id) + candidate = assemble_teacher_navigator_output( + prepared, + { + "facts": ["confirmed field concern"], + "missing": ["current alertness"], + "observe": ["current alertness"], + "checklist": ["cite retrieved protocol cards"], + "uncertain": ["vitals incomplete"], + "sbar": { + "situation": "ignored by v3 deterministic handoff", + "background": "ignored by v3 deterministic handoff", + "assessment_observations_only": "ignored by v3 deterministic handoff", + "handoff_request": "ignored by v3 deterministic handoff", + }, + "script": "I am collecting protocol observations.", + }, + ) + result = score_candidate(candidate, prepared) + base_row = build_sft_row( + prepared=prepared, + result=result, + teacher_model_id="teacher-test", + candidate_total=1, + candidate_passed=1, + ) + spec_record = case_spec_record(prepared) + repair_row = build_repair_row(base_row, spec_record, "missing_observations") + assert repair_row is not None + + dataset = tmp_path / "rows.jsonl" + case_specs = tmp_path / "specs.jsonl" + dataset.write_text( + json.dumps(base_row, sort_keys=True) + "\n" + json.dumps(repair_row, sort_keys=True) + "\n", + encoding="utf-8", + ) + case_specs.write_text(json.dumps(spec_record, sort_keys=True) + "\n", encoding="utf-8") + + summary = verify_rows(dataset_path=dataset, case_specs_path=case_specs) + + assert summary["passed"] is True diff --git a/tests/test_finetune_v5_data_plan.py b/tests/test_finetune_v5_data_plan.py new file mode 100644 index 0000000000000000000000000000000000000000..94a98b55952a33925b7fd985561c9d1fd45189e1 --- /dev/null +++ b/tests/test_finetune_v5_data_plan.py @@ -0,0 +1,197 @@ +import json +from collections import Counter +from pathlib import Path + + +def _accepted_v5_row(): + from figment.observation_targets import required_observation_targets + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import assemble_teacher_navigator_output + from scripts.generate_finetune_data import build_sft_row + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + from scripts.generate_finetune_data import score_candidate + from scripts.generate_finetune_data import v5_required_selected_observation_ids + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(0, cards_by_id, dataset_version="figment_sft_v5") + prepared = prepare_case(spec, cards_by_id) + candidate = assemble_teacher_navigator_output( + prepared, + { + "facts": ["confirmed field concern"], + "missing": ["highest-value observation pending"], + "observe": ["highest-value observation pending"], + "checklist": ["cite deterministic rule cards"], + "uncertain": ["some vitals remain incomplete"], + "sbar": { + "situation": "confirmed handoff concern", + "background": "field workflow setting", + "assessment_observations_only": "observations only from confirmed intake", + "handoff_request": "request protocol review", + }, + "script": "I am checking protocol observations.", + }, + ) + selected_ids = v5_required_selected_observation_ids( + source_card_ids=[str(card_id) for card_id in candidate.get("source_cards", [])], + retrieved_cards=prepared.retrieved_cards, + ) + required_targets_by_id = {str(target["id"]): target for target in required_observation_targets(prepared.retrieved_cards)} + required_observation_text = [ + str(required_targets_by_id[selected_id]["display_text"]) + for selected_id in selected_ids + if selected_id in required_targets_by_id + ] + candidate["selected_required_observation_ids"] = selected_ids + candidate["missing_info_to_collect"] = required_observation_text + list(candidate["missing_info_to_collect"]) + candidate["next_observations_to_collect"] = required_observation_text + result = score_candidate(candidate, prepared) + assert result.passed is True + row = build_sft_row( + prepared=prepared, + result=result, + teacher_model_id="teacher-test", + candidate_total=1, + candidate_passed=1, + ) + return row, case_spec_record(prepared) + + +def test_v5_failure_distribution_matches_focused_plan(): + from scripts.generate_finetune_data import V5_FOCUSED_COUNTS + from scripts.generate_finetune_data import _failure_class_for_index + + categories = Counter(_failure_class_for_index(index, dataset_version="figment_sft_v5") for index in range(1100)) + + assert categories == V5_FOCUSED_COUNTS + + +def test_v5_full_corpus_wrapper_pins_v5_defaults(): + from scripts.generate_v5_full_corpus import DEFAULT_ARGS + from scripts.generate_v5_full_corpus import DEFAULT_COUNTS + from scripts.generate_v5_full_corpus import DEFAULT_NAVIGATOR_COUNT + from scripts.generate_v5_full_corpus import DEFAULT_OUTPUT_VERSION + from scripts.generate_v5_full_corpus import DEFAULT_TEACHER_MODEL_ID + from scripts.generate_v5_full_corpus import build_corpus_args + + assert DEFAULT_OUTPUT_VERSION == "figment_sft_v5" + assert DEFAULT_TEACHER_MODEL_ID == "nvidia/nemotron-3-ultra-550b-a55b:free" + assert DEFAULT_COUNTS == { + "sbar_observation_ownership": 350, + "required_observation_id_selection": 250, + "source_card_invariant": 150, + "noisy_field_audio_style": 100, + "general_regression": 250, + } + assert DEFAULT_NAVIGATOR_COUNT == 1100 + assert DEFAULT_ARGS[DEFAULT_ARGS.index("--dataset-version") + 1] == "figment_sft_v5" + assert DEFAULT_ARGS[DEFAULT_ARGS.index("--teacher-model-id") + 1] == "nvidia/nemotron-3-ultra-550b-a55b:free" + assert DEFAULT_ARGS[DEFAULT_ARGS.index("--navigator-count") + 1] == "1100" + assert DEFAULT_ARGS[DEFAULT_ARGS.index("--repair-count") + 1] == "200" + assert DEFAULT_ARGS[DEFAULT_ARGS.index("--output") + 1] == "data/finetune/figment_sft_v5.jsonl" + assert DEFAULT_ARGS[DEFAULT_ARGS.index("--modal-output-dir") + 1] == "data/finetune/modal/figment_sft_v5" + args = build_corpus_args(["--navigator-count", "2", "--output", "tmp/v5_smoke.jsonl"]) + assert args[-4:] == ["--navigator-count", "2", "--output", "tmp/v5_smoke.jsonl"] + dry_run_args = build_corpus_args(["--navigator-count", "2", "--dry-run"]) + assert dry_run_args[-3:] == ["--navigator-count", "2", "--dry-run"] + + +def test_v5_sft_row_records_training_focus_and_required_observation_ids(): + row, spec_record = _accepted_v5_row() + output = json.loads(row["messages"][1]["content"]) + metadata = row["metadata"] + + assert row["version"] == "figment_sft_v5" + assert row["category"] == "sbar_observation_ownership" + assert metadata["training_focus"] == "sbar_observation_ownership" + assert metadata["excluded_eval_case_ids"] == [ + "field_workflow_holdout_v1-000054", + "field_workflow_holdout_v1-000099", + ] + assert metadata["must_include_source_cards"] + assert set(metadata["must_include_source_cards"]) <= set(output["source_cards"]) + assert output["selected_required_observation_ids"] + assert set(metadata["must_include_selected_required_observation_ids"]) <= set( + output["selected_required_observation_ids"] + ) + assert spec_record["dataset_version"] == "figment_sft_v5" + assert spec_record["workflow_category"] == "sbar_observation_ownership" + + +def test_v5_policy_rejects_missing_fired_card_selected_ids_and_generic_observations(): + from scripts.generate_finetune_data import v5_policy_issues + + output = { + "source_cards": ["SAFETY-BOUNDARIES-v1"], + "missing_info_to_collect": ["repeat vitals"], + "next_observations_to_collect": ["monitor closely"], + "handoff_note_sbar": { + "situation": "", + "background": "", + "assessment_observations_only": "", + "handoff_request": "", + }, + } + retrieved_cards = [ + { + "card_id": "STROKE-SIGNS-v1", + "card": { + "card_id": "STROKE-SIGNS-v1", + "required_observations": ["time last known well"], + }, + } + ] + + issues = v5_policy_issues( + output, + failure_class="source_card_invariant", + expected_red_flag_rule_ids=["STROKE-001"], + expected_candidate_pathway_card_ids=["STROKE-SIGNS-v1"], + structured_intake={}, + rule_results=[{"rule_id": "STROKE-001", "card_id": "STROKE-SIGNS-v1"}], + retrieved_cards=retrieved_cards, + target_protocol_card_id="STROKE-SIGNS-v1", + ) + + assert "fired_rule_source_card_missing:STROKE-SIGNS-v1" in issues + assert "generic_observation_phrase:repeat_vitals" in issues + assert "generic_observation_phrase:monitor_closely" in issues + + +def test_verify_v5_rejects_rows_without_selected_ids(tmp_path): + from scripts.verify_finetune_harness_alignment import verify_rows + + row, spec_record = _accepted_v5_row() + output = json.loads(row["messages"][1]["content"]) + output.pop("selected_required_observation_ids", None) + output["missing_info_to_collect"] = ["repeat vitals"] + output["next_observations_to_collect"] = ["monitor closely"] + row["messages"][1]["content"] = json.dumps(output, sort_keys=True) + + dataset = tmp_path / "rows.jsonl" + case_specs = tmp_path / "specs.jsonl" + dataset.write_text(json.dumps(row, sort_keys=True) + "\n", encoding="utf-8") + case_specs.write_text(json.dumps(spec_record, sort_keys=True) + "\n", encoding="utf-8") + + summary = verify_rows(dataset_path=dataset, case_specs_path=case_specs) + + assert summary["passed"] is False + assert summary["issue_types"]["v5_selected_required_observation_ids_missing"] >= 1 + assert summary["issue_types"]["v5_generic_observation_phrase:repeat_vitals"] >= 1 + + +def test_v5_repair_scope_schedule_targets_observation_and_handoff_repairs(): + from scripts.augment_finetune_repair_rows import _scope_schedule + + counts = Counter(_scope_schedule(200, dataset_version="figment_sft_v5")) + + assert counts == { + "missing_observations": 55, + "handoff_note_sbar": 45, + "citations_and_pathways": 35, + "forbidden_clinical_language": 25, + "protocol_urgency": 20, + "schema": 20, + } diff --git a/tests/test_finetune_v6_data_plan.py b/tests/test_finetune_v6_data_plan.py new file mode 100644 index 0000000000000000000000000000000000000000..413bca45a143505ab5233d2465a4209a84bf69e2 --- /dev/null +++ b/tests/test_finetune_v6_data_plan.py @@ -0,0 +1,183 @@ +import json +from collections import Counter + + +def _accepted_v6_row(): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import assemble_teacher_navigator_output + from scripts.generate_finetune_data import build_sft_row + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + from scripts.generate_finetune_data import score_candidate + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(0, cards_by_id, dataset_version="figment_sft_v6_delta") + prepared = prepare_case(spec, cards_by_id) + candidate = assemble_teacher_navigator_output( + prepared, + { + "facts": ["confirmed field concern"], + "missing": ["confirm current mental status", "record available vital signs"], + "observe": ["confirm current mental status", "record available vital signs"], + "checklist": ["cite deterministic rule cards"], + "uncertain": ["some vitals remain incomplete"], + "sbar": { + "situation": "confirmed handoff concern", + "background": "field workflow setting", + "assessment_observations_only": "observations only from confirmed intake", + "handoff_request": "request protocol review", + }, + "script": "I am checking protocol observations.", + }, + ) + result = score_candidate(candidate, prepared) + assert result.passed is True, result.reward_components + row = build_sft_row( + prepared=prepared, + result=result, + teacher_model_id="teacher-test", + candidate_total=1, + candidate_passed=1, + ) + return row, case_spec_record(prepared) + + +def test_v6_failure_cycle_matches_updated_plan_and_interleaves_smoke_cases(): + from scripts.generate_finetune_data import V6_NAVIGATOR_COUNTS + from scripts.generate_finetune_data import _failure_class_for_index + + categories = Counter( + _failure_class_for_index(index, dataset_version="figment_sft_v6_delta") + for index in range(sum(V6_NAVIGATOR_COUNTS.values())) + ) + first_twelve = { + _failure_class_for_index(index, dataset_version="figment_sft_v6_delta") + for index in range(12) + } + + assert categories == V6_NAVIGATOR_COUNTS + assert {"required_observation_ownership", "observation_correction", "v6_preservation"} <= first_twelve + + +def test_v6_full_corpus_wrapper_pins_delta_defaults(): + from scripts.generate_v6_full_corpus import DEFAULT_OUTPUT_VERSION + from scripts.generate_v6_full_corpus import DEFAULT_REPAIR_COUNT + from scripts.generate_v6_full_corpus import DEFAULT_TEACHER_MODEL_ID + from scripts.generate_v6_full_corpus import build_corpus_args + + assert DEFAULT_OUTPUT_VERSION == "figment_sft_v6_delta" + assert DEFAULT_TEACHER_MODEL_ID == "nvidia/nemotron-3-ultra-550b-a55b:free" + assert DEFAULT_REPAIR_COUNT == 250 + args = build_corpus_args(["--new-delta-count", "10", "--correction-count", "2", "--repair-count", "3", "--dry-run"]) + assert args[args.index("--navigator-count") + 1] == "12" + assert args[args.index("--repair-count") + 1] == "3" + assert args[-1] == "--dry-run" + + +def test_v6_sft_row_records_observation_policy_metadata(): + row, spec_record = _accepted_v6_row() + output = json.loads(row["messages"][1]["content"]) + metadata = row["metadata"] + + assert row["version"] == "figment_sft_v6_delta" + assert row["category"] == "required_observation_ownership" + assert metadata["training_focus"] == "required_observation_ownership" + assert metadata["v6_training_policy_version"] == 1 + assert metadata["required_observation_targets"] + assert output["selected_required_observation_ids"] + assert set(metadata["must_include_selected_required_observation_ids"]) <= set( + output["selected_required_observation_ids"] + ) + assert output["missing_info_to_collect"] != output["next_observations_to_collect"] + observation_text = json.dumps( + output["missing_info_to_collect"] + output["next_observations_to_collect"] + ).lower() + assert "source card ids" not in observation_text + assert spec_record["dataset_version"] == "figment_sft_v6_delta" + assert spec_record["must_include_selected_required_observation_ids"] + + +def test_v6_policy_rejects_duplicate_metadata_and_invisible_selected_ids(): + from scripts.generate_finetune_data import v6_policy_issues + + output = { + "source_cards": ["STROKE-SIGNS-v1"], + "selected_required_observation_ids": ["STROKE-SIGNS-v1::required_observation::1"], + "missing_info_to_collect": [ + "source card IDs", + "deterministic rule results", + "ask about something else", + "monitor closely", + ], + "next_observations_to_collect": [ + "source card IDs", + "deterministic rule results", + "ask about something else", + "monitor closely", + ], + "handoff_note_sbar": { + "situation": "stroke signs", + "background": "field setting", + "assessment_observations_only": "observations pending", + "handoff_request": "request protocol review", + }, + } + retrieved_cards = [ + { + "card_id": "STROKE-SIGNS-v1", + "card": { + "card_id": "STROKE-SIGNS-v1", + "required_observations": ["face droop observation"], + }, + } + ] + + issues = v6_policy_issues( + output, + failure_class="required_observation_ownership", + expected_red_flag_rule_ids=[], + expected_candidate_pathway_card_ids=["STROKE-SIGNS-v1"], + structured_intake={}, + rule_results=[], + retrieved_cards=retrieved_cards, + target_protocol_card_id="STROKE-SIGNS-v1", + ) + + assert "duplicate_long_missing_and_next_observations" in issues + assert any(issue.startswith("harness_metadata_observation:") for issue in issues) + assert "selected_required_observation_id_not_visible:STROKE-SIGNS-v1::required_observation::1" in issues + + +def test_v6_repair_scope_schedule_targets_observation_repairs(): + from scripts.augment_finetune_repair_rows import _scope_schedule + + assert Counter(_scope_schedule(250, dataset_version="figment_sft_v6_delta")) == { + "missing_observations": 250 + } + + +def test_verify_v6_rejects_rows_with_harness_metadata_observations(tmp_path): + from scripts.verify_finetune_harness_alignment import verify_rows + + row, spec_record = _accepted_v6_row() + output = json.loads(row["messages"][1]["content"]) + output["missing_info_to_collect"] = [ + "source card IDs", + "deterministic rule results", + "navigator validation result", + "confirmed intake status", + ] + output["next_observations_to_collect"] = list(output["missing_info_to_collect"]) + row["messages"][1]["content"] = json.dumps(output, sort_keys=True) + + dataset = tmp_path / "rows.jsonl" + case_specs = tmp_path / "specs.jsonl" + dataset.write_text(json.dumps(row, sort_keys=True) + "\n", encoding="utf-8") + case_specs.write_text(json.dumps(spec_record, sort_keys=True) + "\n", encoding="utf-8") + + summary = verify_rows(dataset_path=dataset, case_specs_path=case_specs) + + assert summary["passed"] is False + assert summary["issue_types"]["v6_duplicate_long_missing_and_next_observations"] >= 1 + assert any(key.startswith("v6_harness_metadata_observation") for key in summary["issue_types"]) diff --git a/tests/test_finetune_v7_data_plan.py b/tests/test_finetune_v7_data_plan.py new file mode 100644 index 0000000000000000000000000000000000000000..16b6a9100cd4197c5ca0ea606eecefbc50658225 --- /dev/null +++ b/tests/test_finetune_v7_data_plan.py @@ -0,0 +1,357 @@ +import json +from pathlib import Path + + +def _accepted_v7_row(): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import assemble_teacher_navigator_output + from scripts.generate_finetune_data import build_sft_row + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + from scripts.generate_finetune_data import score_candidate + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(6, cards_by_id, dataset_version="figment_sft_v7_delta") + prepared = prepare_case(spec, cards_by_id) + candidate = assemble_teacher_navigator_output( + prepared, + { + "facts": ["confirmed field concern"], + "missing": ["confirm current mental status", "record available vital signs"], + "observe": ["confirm current mental status", "record available vital signs"], + "checklist": ["cite deterministic rule cards"], + "uncertain": ["some vitals remain incomplete"], + "sbar": { + "situation": "confirmed handoff concern", + "background": "field workflow setting", + "assessment_observations_only": "observations only from confirmed intake", + "handoff_request": "request protocol review", + }, + "script": "I am checking protocol observations.", + }, + ) + result = score_candidate(candidate, prepared) + assert result.passed is True, result.reward_components + row = build_sft_row( + prepared=prepared, + result=result, + teacher_model_id="teacher-test", + candidate_total=1, + candidate_passed=1, + ) + return row, case_spec_record(prepared) + + +def test_v7_source_card_closure_policy_flags_missing_support_and_target_cards(): + from scripts.generate_finetune_data import v7_source_card_closure_issues + + output = { + "source_cards": ["STROKE-SIGNS-v1"], + "safety_boundary": "Use local protocol and do not provide treatment instructions.", + "do_not_do": ["Do not diagnose."], + "handoff_note_sbar": { + "situation": "stroke signs", + "background": "field setting", + "assessment_observations_only": "face droop observed", + "handoff_request": "request protocol review", + }, + } + + issues = v7_source_card_closure_issues(output, target_protocol_card_id="CHEST-PAIN-ESCALATION-v1") + + assert "missing_target_source_card:CHEST-PAIN-ESCALATION-v1" in issues + assert "missing_referral_sbar_source_card" in issues + assert "missing_safety_boundaries_source_card" in issues + + +def test_verify_v7_rejects_missing_referral_sbar_source_card(tmp_path): + from scripts.verify_finetune_harness_alignment import verify_rows + + row, spec_record = _accepted_v7_row() + output = json.loads(row["messages"][1]["content"]) + output["source_cards"] = [card_id for card_id in output["source_cards"] if card_id != "REFERRAL-SBAR-v1"] + row["messages"][1]["content"] = json.dumps(output, sort_keys=True) + + dataset = tmp_path / "rows.jsonl" + case_specs = tmp_path / "specs.jsonl" + dataset.write_text(json.dumps(row, sort_keys=True) + "\n", encoding="utf-8") + case_specs.write_text(json.dumps(spec_record, sort_keys=True) + "\n", encoding="utf-8") + + summary = verify_rows(dataset_path=dataset, case_specs_path=case_specs) + + assert summary["passed"] is False + assert summary["issue_types"]["v7_missing_referral_sbar_source_card"] >= 1 + + +def test_verify_v7_rejects_missing_safety_boundaries_source_card(tmp_path): + from scripts.verify_finetune_harness_alignment import verify_rows + + row, spec_record = _accepted_v7_row() + output = json.loads(row["messages"][1]["content"]) + output["source_cards"] = [card_id for card_id in output["source_cards"] if card_id != "SAFETY-BOUNDARIES-v1"] + row["messages"][1]["content"] = json.dumps(output, sort_keys=True) + + dataset = tmp_path / "rows.jsonl" + case_specs = tmp_path / "specs.jsonl" + dataset.write_text(json.dumps(row, sort_keys=True) + "\n", encoding="utf-8") + case_specs.write_text(json.dumps(spec_record, sort_keys=True) + "\n", encoding="utf-8") + + summary = verify_rows(dataset_path=dataset, case_specs_path=case_specs) + + assert summary["passed"] is False + assert summary["issue_types"]["v7_missing_safety_boundaries_source_card"] >= 1 + + +def test_verify_v7_rejects_missing_target_source_card(tmp_path): + from scripts.verify_finetune_harness_alignment import verify_rows + + row, spec_record = _accepted_v7_row() + output = json.loads(row["messages"][1]["content"]) + target_card_id = spec_record["target_protocol_card_id"] + output["source_cards"] = [card_id for card_id in output["source_cards"] if card_id != target_card_id] + row["messages"][1]["content"] = json.dumps(output, sort_keys=True) + + dataset = tmp_path / "rows.jsonl" + case_specs = tmp_path / "specs.jsonl" + dataset.write_text(json.dumps(row, sort_keys=True) + "\n", encoding="utf-8") + case_specs.write_text(json.dumps(spec_record, sort_keys=True) + "\n", encoding="utf-8") + + summary = verify_rows(dataset_path=dataset, case_specs_path=case_specs) + + assert summary["passed"] is False + assert summary["issue_types"][f"v7_missing_target_source_card:{target_card_id}"] >= 1 + + +def _replay_row( + *, + case_id: str, + output: dict, + category: str = "general_regression", + dataset_version: str = "figment_sft_v6_delta", + task_type: str | None = None, +) -> dict: + metadata = { + "dataset_version": dataset_version, + "validator_passed": True, + "validation_result": {"passed": True, "failures": []}, + "expected_label_score": { + "all_expected_labels_passed": True, + "forbidden_behavior_absent": True, + }, + "must_include_source_cards": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], + } + if task_type: + metadata["task_type"] = task_type + return { + "case_id": case_id, + "category": category, + "version": dataset_version, + "metadata": metadata, + "messages": [ + {"role": "user", "content": "prompt"}, + {"role": "assistant", "content": json.dumps(output, sort_keys=True)}, + ], + } + + +def test_v7_replay_audit_rejects_full_rows_missing_support_cards(): + from scripts.build_v7_replay_corpus import audit_row + + row = _replay_row( + case_id="missing-support", + output={ + "protocol_urgency": "urgent", + "source_cards": ["STROKE-SIGNS-v1"], + "safety_boundary": "Use local protocol and do not provide treatment instructions.", + "handoff_note_sbar": { + "situation": "stroke signs", + "background": "field setting", + "assessment_observations_only": "face droop observed", + "handoff_request": "request protocol review", + }, + "missing_info_to_collect": ["confirm current alertness"], + "next_observations_to_collect": ["confirm current alertness"], + }, + ) + + result = audit_row(row) + + assert result.accepted is False + assert "missing_referral_sbar_source_card" in result.reasons + assert "missing_safety_boundaries_source_card" in result.reasons + + +def test_build_v7_replay_corpus_selects_target_buckets_and_reversions_rows(tmp_path: Path): + from scripts.build_v7_replay_corpus import build_replay_corpus + + clean_full = _replay_row( + case_id="clean-full", + output={ + "protocol_urgency": "urgent", + "source_cards": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], + "safety_boundary": "Use local protocol and do not provide treatment instructions.", + "handoff_note_sbar": { + "situation": "stroke signs", + "background": "field setting", + "assessment_observations_only": "face droop observed", + "handoff_request": "request protocol review", + }, + "missing_info_to_collect": ["confirm current alertness"], + "next_observations_to_collect": ["confirm current alertness"], + }, + ) + clean_repair = _replay_row( + case_id="clean-repair", + output={"source_cards": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"]}, + category="focused_repair:citations_and_pathways", + dataset_version="figment_sft_v3", + task_type="focused_repair", + ) + delta_path = tmp_path / "figment_sft_v6_delta.jsonl" + replay_path = tmp_path / "figment_sft_v6_replay.jsonl" + delta_path.write_text(json.dumps(clean_full, sort_keys=True) + "\n", encoding="utf-8") + replay_path.write_text(json.dumps(clean_repair, sort_keys=True) + "\n", encoding="utf-8") + + output_path = tmp_path / "selected.jsonl" + manifest_path = tmp_path / "manifest.json" + summary = build_replay_corpus( + input_paths=[delta_path, replay_path], + output_path=output_path, + manifest_path=manifest_path, + targets={"figment_sft_v6_delta": 1, "figment_sft_v6_replay": 1}, + seed="test", + ) + rows = [json.loads(line) for line in output_path.read_text(encoding="utf-8").splitlines()] + + assert summary["selected_rows"] == 2 + assert summary["selected_by_source_bucket"] == { + "figment_sft_v6_delta": 1, + "figment_sft_v6_replay": 1, + } + assert {row["version"] for row in rows} == {"figment_sft_v7_replay"} + assert all(row["metadata"]["v7_replay_audit"]["accepted"] is True for row in rows) + + +def test_v7_failure_cycle_matches_planned_navigator_counts(): + from scripts.generate_finetune_data import V7_NAVIGATOR_COUNTS + from scripts.generate_finetune_data import _failure_class_for_index + + counts = { + name: sum( + 1 + for index in range(sum(V7_NAVIGATOR_COUNTS.values())) + if _failure_class_for_index(index, dataset_version="figment_sft_v7_delta") == name + ) + for name in V7_NAVIGATOR_COUNTS + } + + assert counts == V7_NAVIGATOR_COUNTS + assert { + _failure_class_for_index(index, dataset_version="figment_sft_v7_delta") + for index in range(20) + } == set(V7_NAVIGATOR_COUNTS) + + +def test_v7_prepare_case_retrieves_mandatory_support_cards(): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import SAFETY_CARD_ID + from scripts.generate_finetune_data import SBAR_CARD_ID + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(0, cards_by_id, dataset_version="figment_sft_v7_delta") + prepared = prepare_case(spec, cards_by_id) + + assert spec.failure_class == "source_card_closure" + assert SAFETY_CARD_ID in prepared.retrieved_ids + assert SBAR_CARD_ID in prepared.retrieved_ids + assert SAFETY_CARD_ID in prepared.expected_source_card_ids + assert SBAR_CARD_ID in prepared.expected_source_card_ids + + +def test_v7_repair_scope_schedule_matches_planned_counts(): + from collections import Counter + + from scripts.augment_finetune_repair_rows import V7_REPAIR_SCOPE_DISTRIBUTION + from scripts.augment_finetune_repair_rows import _scope_schedule + + schedule = _scope_schedule(240, dataset_version="figment_sft_v7_delta") + + assert Counter(schedule) == dict(V7_REPAIR_SCOPE_DISTRIBUTION) + + +def test_generate_v7_full_corpus_defaults_and_overrides(): + from scripts.generate_v7_full_corpus import DEFAULT_NAVIGATOR_COUNT + from scripts.generate_v7_full_corpus import build_corpus_args + + defaults = build_corpus_args([]) + overridden = build_corpus_args(["--navigator-count", "12", "--repair-count", "5", "--dry-run"]) + + assert defaults[defaults.index("--dataset-version") + 1] == "figment_sft_v7_delta" + assert defaults[defaults.index("--navigator-count") + 1] == str(DEFAULT_NAVIGATOR_COUNT) + assert defaults[defaults.index("--output") + 1] == "data/finetune/figment_sft_v7_delta.jsonl" + assert overridden[overridden.index("--navigator-count") + 1] == "12" + assert overridden[overridden.index("--repair-count") + 1] == "5" + assert "--dry-run" in overridden + + +def test_merge_v7_corpus_resolves_replay_case_specs(tmp_path: Path, monkeypatch): + import scripts.merge_v7_training_corpus as merge_v7 + + delta_row = _replay_row( + case_id="figment_sft_v7_delta-080000", + output={ + "protocol_urgency": "urgent", + "source_cards": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], + }, + category="source_card_closure", + dataset_version="figment_sft_v7_delta", + ) + replay_row = _replay_row( + case_id="figment_sft_v6_delta-070000", + output={ + "protocol_urgency": "urgent", + "source_cards": ["STROKE-SIGNS-v1", "SAFETY-BOUNDARIES-v1", "REFERRAL-SBAR-v1"], + }, + category="required_observation_ownership", + dataset_version="figment_sft_v7_replay", + ) + replay_row["metadata"]["v7_replay_audit"] = { + "accepted": True, + "original_source_dataset_version": "figment_sft_v6_delta", + "source_bucket": "figment_sft_v6_delta", + } + + delta_path = tmp_path / "delta.jsonl" + replay_path = tmp_path / "replay.jsonl" + delta_specs = tmp_path / "delta_specs.jsonl" + output = tmp_path / "merged.jsonl" + specs = tmp_path / "merged_specs.jsonl" + manifest = tmp_path / "manifest.json" + source_specs = tmp_path / "v6_delta_specs.jsonl" + delta_path.write_text(json.dumps(delta_row, sort_keys=True) + "\n", encoding="utf-8") + replay_path.write_text(json.dumps(replay_row, sort_keys=True) + "\n", encoding="utf-8") + delta_specs.write_text( + json.dumps({"case_id": "figment_sft_v7_delta-080000", "structured_intake": {}}, sort_keys=True) + "\n", + encoding="utf-8", + ) + source_specs.write_text( + json.dumps({"case_id": "figment_sft_v6_delta-070000", "structured_intake": {}}, sort_keys=True) + "\n", + encoding="utf-8", + ) + monkeypatch.setitem(merge_v7.SOURCE_CASE_SPECS, "figment_sft_v6_delta", source_specs) + + summary = merge_v7.merge_v7_corpus( + delta_path=delta_path, + delta_case_specs_path=delta_specs, + replay_path=replay_path, + output_path=output, + case_specs_path=specs, + manifest_path=manifest, + dataset_version="figment_sft_v7", + ) + + assert summary["row_count"] == 2 + assert summary["replay_source_counts"] == {"figment_sft_v6_delta": 1} diff --git a/tests/test_finetune_v8_data_plan.py b/tests/test_finetune_v8_data_plan.py new file mode 100644 index 0000000000000000000000000000000000000000..ab0419b7c593c3cc77050195671792d869ed93ed --- /dev/null +++ b/tests/test_finetune_v8_data_plan.py @@ -0,0 +1,101 @@ +import json +from collections import Counter + + +def _accepted_v8_row(): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import assemble_teacher_navigator_output + from scripts.generate_finetune_data import build_sft_row + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + from scripts.generate_finetune_data import score_candidate + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(0, cards_by_id, dataset_version="figment_sft_v8_delta") + prepared = prepare_case(spec, cards_by_id) + candidate = assemble_teacher_navigator_output( + prepared, + { + "facts": ["postpartum fever confirmed", "temperature elevated"], + "missing": ["pregnancy or postpartum status", "bleeding report", "temperature if available"], + "observe": ["temperature if available", "bleeding report", "mental status"], + "checklist": ["cite fever and pregnancy cards"], + "uncertain": ["blood pressure pending"], + "sbar": { + "situation": "postpartum fever", + "background": "field workflow setting", + "assessment_observations_only": "fever and postpartum context confirmed", + "handoff_request": "request protocol review", + }, + "script": "I am checking fever and postpartum observations.", + }, + ) + result = score_candidate(candidate, prepared) + assert result.passed is True, result.reward_components + row = build_sft_row( + prepared=prepared, + result=result, + teacher_model_id="teacher-test", + candidate_total=1, + candidate_passed=1, + ) + return row, case_spec_record(prepared) + + +def test_v8_failure_cycle_targets_multirule_observation_ownership(): + from scripts.generate_finetune_data import V8_NAVIGATOR_COUNTS + from scripts.generate_finetune_data import _failure_class_for_index + + categories = Counter( + _failure_class_for_index(index, dataset_version="figment_sft_v8_delta") + for index in range(sum(V8_NAVIGATOR_COUNTS.values())) + ) + first_twelve = { + _failure_class_for_index(index, dataset_version="figment_sft_v8_delta") + for index in range(12) + } + + assert categories == V8_NAVIGATOR_COUNTS + assert {"multi_rule_observation_ownership", "multi_rule_candidate_focus"} <= first_twelve + + +def test_v8_sft_row_requires_all_fired_clinical_observation_ids(): + row, spec_record = _accepted_v8_row() + output = json.loads(row["messages"][1]["content"]) + metadata = row["metadata"] + selected_ids = set(output["selected_required_observation_ids"]) + + assert row["version"] == "figment_sft_v8_delta" + assert spec_record["dataset_version"] == "figment_sft_v8_delta" + assert spec_record["target_protocol_card_id"] == "FEVER-RED-FLAGS-v1" + assert {"PREG-001", "FEVER-001"} <= set(spec_record["expected_red_flag_rule_ids"]) + assert "PREG-DANGER-SIGNS-v1" in output["source_cards"] + candidate_ids = [item["card_id"] for item in output["candidate_protocol_pathways"]] + assert candidate_ids == ["FEVER-RED-FLAGS-v1", "PREG-DANGER-SIGNS-v1"] + assert any(item.startswith("FEVER-RED-FLAGS-v1::required_observation::") for item in selected_ids) + assert any(item.startswith("PREG-DANGER-SIGNS-v1::required_observation::") for item in selected_ids) + assert set(metadata["must_include_selected_required_observation_ids"]) <= selected_ids + observation_text = json.dumps( + output["missing_info_to_collect"] + output["next_observations_to_collect"] + ).lower() + for cue in ("temperature if available", "pregnancy or postpartum status", "bleeding report", "fever report"): + assert cue in observation_text + assert metadata["v7_training_policy_version"] == 1 + + +def test_v8_full_corpus_wrapper_pins_delta_defaults(): + from scripts.generate_v8_full_corpus import DEFAULT_NAVIGATOR_COUNT + from scripts.generate_v8_full_corpus import DEFAULT_OUTPUT_VERSION + from scripts.generate_v8_full_corpus import DEFAULT_REPAIR_COUNT + from scripts.generate_v8_full_corpus import DEFAULT_TEACHER_MODEL_ID + from scripts.generate_v8_full_corpus import build_corpus_args + + assert DEFAULT_OUTPUT_VERSION == "figment_sft_v8_delta" + assert DEFAULT_TEACHER_MODEL_ID == "nvidia/nemotron-3-ultra-550b-a55b:free" + assert DEFAULT_NAVIGATOR_COUNT == 400 + assert DEFAULT_REPAIR_COUNT == 0 + args = build_corpus_args(["--navigator-count", "8", "--repair-count", "0", "--dry-run"]) + assert args[args.index("--navigator-count") + 1] == "8" + assert args[args.index("--repair-count") + 1] == "0" + assert args[-1] == "--dry-run" diff --git a/tests/test_finetune_v9_data_plan.py b/tests/test_finetune_v9_data_plan.py new file mode 100644 index 0000000000000000000000000000000000000000..b7c8e68d2bf5fd8e32dfd9861025d898b257071b --- /dev/null +++ b/tests/test_finetune_v9_data_plan.py @@ -0,0 +1,122 @@ +import json +from collections import Counter + + +def _accepted_v9_row(): + from figment.retrieval import load_protocol_cards + from scripts.generate_finetune_data import assemble_teacher_navigator_output + from scripts.generate_finetune_data import build_sft_row + from scripts.generate_finetune_data import case_spec_record + from scripts.generate_finetune_data import generate_case_spec + from scripts.generate_finetune_data import prepare_case + from scripts.generate_finetune_data import score_candidate + + cards_by_id = {str(card["card_id"]): card for card in load_protocol_cards()} + spec = generate_case_spec(0, cards_by_id, dataset_version="figment_sft_v9_delta") + prepared = prepare_case(spec, cards_by_id) + candidate = assemble_teacher_navigator_output( + prepared, + { + "facts": ["postpartum two weeks", "fever with chills", "temperature elevated"], + "missing": [ + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + "temperature if available", + ], + "observe": ["temperature if available", "bleeding report", "abdominal pain report"], + "checklist": ["cite fever and pregnancy danger-sign cards"], + "uncertain": ["blood pressure pending"], + "sbar": { + "situation": "postpartum fever", + "background": "two weeks postpartum in field intake", + "assessment_observations_only": "fever and postpartum context confirmed", + "handoff_request": "request protocol review", + }, + "script": "I am checking fever and postpartum danger-sign observations.", + }, + ) + result = score_candidate(candidate, prepared) + assert result.passed is True, result.reward_components + row = build_sft_row( + prepared=prepared, + result=result, + teacher_model_id="teacher-test", + candidate_total=1, + candidate_passed=1, + ) + return row, case_spec_record(prepared) + + +def test_v9_failure_cycle_targets_remaining_v8_required_obs_gap(): + from scripts.generate_finetune_data import V9_NAVIGATOR_COUNTS + from scripts.generate_finetune_data import _failure_class_for_index + + categories = Counter( + _failure_class_for_index(index, dataset_version="figment_sft_v9_delta") + for index in range(sum(V9_NAVIGATOR_COUNTS.values())) + ) + first_twelve = { + _failure_class_for_index(index, dataset_version="figment_sft_v9_delta") + for index in range(12) + } + + assert categories == V9_NAVIGATOR_COUNTS + assert { + "postpartum_fever_required_obs_cross_category", + "postpartum_fever_required_obs_candidate_focus", + } <= first_twelve + + +def test_v9_sft_row_requires_postpartum_fever_and_preg_observation_text(): + row, spec_record = _accepted_v9_row() + output = json.loads(row["messages"][1]["content"]) + metadata = row["metadata"] + selected_ids = set(output["selected_required_observation_ids"]) + + assert row["version"] == "figment_sft_v9_delta" + assert spec_record["dataset_version"] == "figment_sft_v9_delta" + assert spec_record["target_protocol_card_id"] == "FEVER-RED-FLAGS-v1" + assert {"PREG-001", "FEVER-001"} <= set(spec_record["expected_red_flag_rule_ids"]) + assert "postpartum two weeks" in json.dumps(spec_record["structured_intake"]).lower() + assert "PREG-DANGER-SIGNS-v1" in output["source_cards"] + assert "FEVER-RED-FLAGS-v1" in output["source_cards"] + assert [item["card_id"] for item in output["candidate_protocol_pathways"]] == [ + "FEVER-RED-FLAGS-v1", + "PREG-DANGER-SIGNS-v1", + ] + assert any(item.startswith("FEVER-RED-FLAGS-v1::required_observation::") for item in selected_ids) + assert any(item.startswith("PREG-DANGER-SIGNS-v1::required_observation::") for item in selected_ids) + assert set(metadata["must_include_selected_required_observation_ids"]) <= selected_ids + + observation_text = json.dumps(output["missing_info_to_collect"]).lower() + for cue in ( + "temperature if available", + "pregnancy or postpartum status", + "bleeding report", + "abdominal pain report", + "headache or vision symptoms", + "seizure or fainting report", + "fever report", + ): + assert cue in observation_text + + +def test_v9_full_corpus_wrapper_pins_delta_defaults(): + from scripts.generate_v9_full_corpus import DEFAULT_NAVIGATOR_COUNT + from scripts.generate_v9_full_corpus import DEFAULT_OUTPUT_VERSION + from scripts.generate_v9_full_corpus import DEFAULT_REPAIR_COUNT + from scripts.generate_v9_full_corpus import DEFAULT_TEACHER_MODEL_ID + from scripts.generate_v9_full_corpus import build_corpus_args + + assert DEFAULT_OUTPUT_VERSION == "figment_sft_v9_delta" + assert DEFAULT_TEACHER_MODEL_ID == "nvidia/nemotron-3-ultra-550b-a55b:free" + assert DEFAULT_NAVIGATOR_COUNT == 400 + assert DEFAULT_REPAIR_COUNT == 0 + args = build_corpus_args(["--navigator-count", "8", "--repair-count", "0", "--dry-run"]) + assert args[args.index("--navigator-count") + 1] == "8" + assert args[args.index("--repair-count") + 1] == "0" + assert args[-1] == "--dry-run" diff --git a/tests/test_local_4b_evidence_script.py b/tests/test_local_4b_evidence_script.py new file mode 100644 index 0000000000000000000000000000000000000000..8715735266ff14d8f91c107cab2ccba3f38fa109 --- /dev/null +++ b/tests/test_local_4b_evidence_script.py @@ -0,0 +1,225 @@ +import json +from pathlib import Path +from typing import Any + +from scripts import run_local_4b_evidence + + +class _FakeResponse: + def __init__(self, payload: dict[str, Any]) -> None: + self.payload = payload + + def __enter__(self) -> "_FakeResponse": + return self + + def __exit__(self, *_: Any) -> None: + return None + + def read(self) -> bytes: + return json.dumps(self.payload).encode("utf-8") + + +def test_normalize_base_url_accepts_models_or_chat_url() -> None: + assert ( + run_local_4b_evidence._normalize_base_url("http://local-runtime.local:8001/v1/models") + == "http://local-runtime.local:8001/v1" + ) + assert ( + run_local_4b_evidence._normalize_base_url("http://local-runtime.local:8001/v1/chat/completions") + == "http://local-runtime.local:8001/v1" + ) + + +def test_endpoint_failure_writes_summary_without_running_smoke( + tmp_path: Path, + monkeypatch, +) -> None: + def fake_urlopen(*_: Any, **__: Any) -> _FakeResponse: + raise OSError("no route") + + def fail_smoke() -> dict[str, Any]: + raise AssertionError("smoke should not run if /v1/models is unavailable") + + monkeypatch.setattr("urllib.request.urlopen", fake_urlopen) + monkeypatch.setattr(run_local_4b_evidence, "run_smoke", fail_smoke) + + summary = run_local_4b_evidence.run_evidence( + base_url="http://local-runtime.local:8001/v1", + model_id="nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16", + output_dir=tmp_path, + case_paths=[], + limit=None, + timeout_seconds=0.1, + ) + + assert summary["status"] == "endpoint_unavailable" + assert summary["counts_as_no_cloud_route_proof"] is False + assert summary["counts_as_50_case_local_llm_competence"] is False + assert (tmp_path / "endpoint_metadata.json").exists() + assert (tmp_path / "summary.json").exists() + + +def test_smoke_failure_skips_eval_by_default(tmp_path: Path, monkeypatch) -> None: + monkeypatch.setattr( + "urllib.request.urlopen", + lambda *_args, **_kwargs: _FakeResponse({"data": [{"id": "nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16"}]}), + ) + monkeypatch.setattr( + run_local_4b_evidence, + "run_smoke", + lambda: { + "status": "failed", + "local_llm_evidence": { + "counts_as_no_cloud_route_proof": False, + "counts_as_50_case_local_llm_competence": False, + }, + }, + ) + + def fail_eval(*_: Any, **__: Any) -> dict[str, Any]: + raise AssertionError("eval should be skipped when smoke fails") + + monkeypatch.setattr(run_local_4b_evidence, "run_eval", fail_eval) + + summary = run_local_4b_evidence.run_evidence( + base_url="http://local-runtime.local:8001/v1", + model_id="nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16", + output_dir=tmp_path, + case_paths=[], + limit=None, + timeout_seconds=1.0, + ) + + assert summary["status"] == "smoke_failed_eval_skipped" + assert summary["eval_skip_reason"] == "route smoke did not prove configured-model validation" + assert (tmp_path / "route_smoke.json").exists() + + +def test_smoke_only_pass_records_route_proof(tmp_path: Path, monkeypatch) -> None: + monkeypatch.setattr( + "urllib.request.urlopen", + lambda *_args, **_kwargs: _FakeResponse({"data": [{"id": "nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16"}]}), + ) + monkeypatch.setattr( + run_local_4b_evidence, + "run_smoke", + lambda: { + "status": "passed", + "local_llm_evidence": { + "counts_as_no_cloud_route_proof": True, + "counts_as_50_case_local_llm_competence": False, + }, + }, + ) + + summary = run_local_4b_evidence.run_evidence( + base_url="http://local-runtime.local:8001/v1/models", + model_id="nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16", + output_dir=tmp_path, + case_paths=[], + limit=None, + timeout_seconds=1.0, + smoke_only=True, + ) + + assert summary["status"] == "smoke_passed" + assert summary["base_url"] == "http://local-runtime.local:8001/v1" + assert summary["counts_as_no_cloud_route_proof"] is True + assert summary["counts_as_50_case_local_llm_competence"] is False + + +def test_completed_eval_writes_evidence_manifest(tmp_path: Path, monkeypatch) -> None: + monkeypatch.setattr( + "urllib.request.urlopen", + lambda *_args, **_kwargs: _FakeResponse({"data": [{"id": "nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16"}]}), + ) + monkeypatch.setattr( + run_local_4b_evidence, + "run_smoke", + lambda: { + "status": "passed", + "local_llm_evidence": { + "counts_as_no_cloud_route_proof": True, + "counts_as_50_case_local_llm_competence": False, + }, + }, + ) + + def fake_run_eval(*, output_path: Path, **_: Any) -> dict[str, Any]: + records = [ + { + "case_id": "case-1", + "raw_configured_model_success": True, + "repair_success": False, + "canned_fallback_used": False, + "competence_success": True, + "latency_ms": 10.0, + "trace_hash": "trace-a", + }, + { + "case_id": "case-2", + "raw_configured_model_success": False, + "repair_success": False, + "canned_fallback_used": True, + "competence_success": False, + "latency_ms": 30.0, + "trace_hash": "trace-b", + }, + ] + output_path.write_text( + "".join(f"{json.dumps(record, sort_keys=True)}\n" for record in records), + encoding="utf-8", + ) + return { + "total_cases": 2, + "raw_configured_model_successes": 1, + "repair_successes": 0, + "competence_successes": 1, + "fallback_uses": 1, + "canned_fallback_uses": 1, + "final_validation_successes": 2, + "records_with_field_provenance": 2, + "field_provenance_fields": 26, + "field_provenance_counts": {"model_raw": 13, "deterministic_fallback": 13}, + "model_retained_field_count": 13, + "visible_field_provenance_count": 26, + "model_visible_field_count": 13, + "deterministic_patch_count": 13, + "model_field_pass_rate": 0.5, + "model_visible_fields_retained": 0.5, + "local_llm_evidence": { + "counts_as_50_case_local_llm_eval": False, + "counts_as_50_case_local_llm_competence": False, + }, + } + + monkeypatch.setattr(run_local_4b_evidence, "run_eval", fake_run_eval) + + summary = run_local_4b_evidence.run_evidence( + base_url="http://192.168.1.7:8001/v1", + model_id="nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16", + output_dir=tmp_path, + case_paths=[], + limit=None, + timeout_seconds=1.0, + ) + + manifest_path = Path(summary["eval_evidence_manifest_path"]) + manifest = json.loads(manifest_path.read_text(encoding="utf-8")) + + assert summary["status"] == "eval_completed" + assert summary["trace_hash_count"] == 2 + assert summary["latency_ms"]["mean"] == 20.0 + assert manifest["model_server_metadata"]["advertised_model_ids"] == [ + "nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16" + ] + assert manifest["no_cloud_evidence"]["base_url_host_class"] == "private_lan" + assert manifest["score_summary"]["raw_configured_model_successes"] == 1 + assert manifest["score_summary"]["canned_fallback_uses"] == 1 + assert manifest["case_ids"]["raw_success"] == ["case-1"] + assert manifest["case_ids"]["full_fallback"] == ["case-2"] + assert manifest["field_provenance"]["model_field_pass_rate"] == 0.5 + assert manifest["trace_hashes"] == [ + {"case_id": "case-1", "trace_hash": "trace-a"}, + {"case_id": "case-2", "trace_hash": "trace-b"}, + ] diff --git a/tests/test_local_asr_evidence_script.py b/tests/test_local_asr_evidence_script.py new file mode 100644 index 0000000000000000000000000000000000000000..459153fc863a485092aa390fc2c8a1f706d906af --- /dev/null +++ b/tests/test_local_asr_evidence_script.py @@ -0,0 +1,110 @@ +import json +from pathlib import Path +import wave + +from scripts import run_local_asr_evidence + + +def _provider_payload(path: Path) -> Path: + payload = { + "transcript": "Local Parakeet transcript says the patient has trouble breathing.", + "suggested_fields": [ + { + "field": "symptoms", + "draft_value": "trouble breathing", + "source_snippet": "trouble breathing", + } + ], + "missing_or_unclear_fields": ["vitals"], + "provisional_red_flag_mentions": ["trouble breathing"], + } + path.write_text(json.dumps(payload), encoding="utf-8") + return path + + +def test_asr_evidence_without_provider_payload_records_artifact_only(tmp_path: Path, monkeypatch) -> None: + artifact_path = tmp_path / "parakeet-rnnt-1.1b.nemo" + artifact_path.write_bytes(b"fake parakeet") + monkeypatch.setattr(run_local_asr_evidence, "PARAKEET_NEMO_PATH", artifact_path) + monkeypatch.setattr(run_local_asr_evidence, "PARAKEET_NEMO_BYTES", len(b"fake parakeet")) + monkeypatch.setattr( + run_local_asr_evidence, + "PARAKEET_NEMO_SHA256", + run_local_asr_evidence._sha256(artifact_path), + ) + + summary = run_local_asr_evidence.run_evidence(output_dir=tmp_path / "evidence") + + assert summary["status"] == "artifact_present_provider_payload_required" + assert summary["counts_as_local_asr_artifact"] is True + assert summary["counts_as_local_asr_proof"] is False + assert (tmp_path / "evidence" / "artifact_metadata.json").exists() + assert summary["asr_evidence_manifest_path"] == str(tmp_path / "evidence" / "asr_evidence_manifest.json") + manifest = json.loads((tmp_path / "evidence" / "asr_evidence_manifest.json").read_text(encoding="utf-8")) + assert manifest["proof_flags"]["counts_as_local_asr_artifact"] is True + assert manifest["proof_flags"]["counts_as_local_asr_proof"] is False + assert manifest["provider_payload"] is None + + +def test_asr_evidence_provider_payload_can_pass_gated_draft_checks(tmp_path: Path, monkeypatch) -> None: + artifact_path = tmp_path / "parakeet-rnnt-1.1b.nemo" + artifact_path.write_bytes(b"fake parakeet") + monkeypatch.setattr(run_local_asr_evidence, "PARAKEET_NEMO_PATH", artifact_path) + monkeypatch.setattr(run_local_asr_evidence, "PARAKEET_NEMO_BYTES", len(b"fake parakeet")) + monkeypatch.setattr( + run_local_asr_evidence, + "PARAKEET_NEMO_SHA256", + run_local_asr_evidence._sha256(artifact_path), + ) + payload_path = _provider_payload(tmp_path / "provider.json") + + summary = run_local_asr_evidence.run_evidence( + output_dir=tmp_path / "evidence", + provider_payload_path=payload_path, + provider_note="local adapter smoke", + ) + + assert summary["status"] == "local_asr_proof_passed" + assert summary["counts_as_local_asr_artifact"] is True + assert summary["counts_as_local_asr_proof"] is True + draft = json.loads((tmp_path / "evidence" / "audio_draft.json").read_text(encoding="utf-8")) + assert draft["transcript_source"] == "local_parakeet_asr_provider" + assert draft["raw_audio_stored"] is False + manifest = json.loads((tmp_path / "evidence" / "asr_evidence_manifest.json").read_text(encoding="utf-8")) + assert manifest["evidence_version"] == 1 + assert manifest["provider_payload"]["sha256"] == run_local_asr_evidence._sha256(payload_path) + assert manifest["draft_summary"]["transcript_hash"] + assert manifest["draft_summary"]["suggested_field_count"] == 1 + assert manifest["draft_checks"]["counts_as_local_asr_proof"] is True + assert manifest["configured_route"]["audio_backend"] == "parakeet_nemo" + assert manifest["configured_route"]["model_stack"] == "local_4b_parakeet" + assert manifest["raw_audio_handling"]["raw_audio_copied_to_evidence"] is False + assert manifest["raw_audio_handling"]["raw_audio_stored"] is False + + +def test_asr_evidence_audio_metadata_hashes_without_copying_audio(tmp_path: Path, monkeypatch) -> None: + artifact_path = tmp_path / "parakeet-rnnt-1.1b.nemo" + artifact_path.write_bytes(b"fake parakeet") + monkeypatch.setattr(run_local_asr_evidence, "PARAKEET_NEMO_PATH", artifact_path) + monkeypatch.setattr(run_local_asr_evidence, "PARAKEET_NEMO_BYTES", len(b"fake parakeet")) + monkeypatch.setattr( + run_local_asr_evidence, + "PARAKEET_NEMO_SHA256", + run_local_asr_evidence._sha256(artifact_path), + ) + audio_path = tmp_path / "source.wav" + with wave.open(str(audio_path), "wb") as wav: + wav.setnchannels(1) + wav.setsampwidth(2) + wav.setframerate(8000) + wav.writeframes(b"\0\0" * 8000) + + summary = run_local_asr_evidence.run_evidence(output_dir=tmp_path / "evidence", audio_path=audio_path) + + assert summary["counts_as_local_asr_proof"] is False + audio_metadata = json.loads((tmp_path / "evidence" / "audio_metadata.json").read_text(encoding="utf-8")) + assert audio_metadata["duration_seconds"] == 1.0 + assert audio_metadata["raw_audio_copied_to_evidence"] is False + manifest = json.loads((tmp_path / "evidence" / "asr_evidence_manifest.json").read_text(encoding="utf-8")) + assert manifest["raw_audio_handling"]["audio_metadata_sha256"] == audio_metadata["sha256"] + assert manifest["raw_audio_handling"]["raw_audio_copied_to_evidence"] is False diff --git a/tests/test_modal_eval_batch.py b/tests/test_modal_eval_batch.py new file mode 100644 index 0000000000000000000000000000000000000000..7dbbaabafe6df18a9de8edff2c9804f9a8626697 --- /dev/null +++ b/tests/test_modal_eval_batch.py @@ -0,0 +1,33 @@ +import importlib.util +from pathlib import Path + + +def _load_modal_eval_module(): + module_path = Path(__file__).resolve().parents[1] / "modal" / "eval_figment_nemotron.py" + spec = importlib.util.spec_from_file_location("figment_modal_eval", module_path) + assert spec is not None + module = importlib.util.module_from_spec(spec) + assert spec.loader is not None + spec.loader.exec_module(module) + return module + + +def test_modal_eval_config_points_at_v5_merged_checkpoint_and_result_volume(): + module = _load_modal_eval_module() + + config = module.build_eval_config(output_name="unit-v5-eval") + + assert config["checkpoint_model_dir"] == "/checkpoints/figment_sft_v5/figment-sft-v5-lora-merged-bf16" + assert config["checkpoint_artifact"] == ( + "figment-checkpoints:/figment_sft_v5/figment-sft-v5-lora-merged-bf16" + ) + assert config["output_dir"] == "/eval_results/unit-v5-eval" + assert config["gguf_model_path"] == ( + "/eval_results/model_cache/figment_sft_v5/figment-sft-v5-lora-merged-bf16.bf16.gguf" + ) + assert config["result_volume_name"] == "figment-eval-results" + assert config["runtime"] == "llama_cpp_cuda" + assert config["cuda_architectures"] == "90" + assert config["case_paths"] == ["/tmp/figment_eval_cases/field_workflow_holdout_v1.jsonl"] + assert config["expected_case_count"] == 150 + assert config["max_generation_tokens"] == 1536 diff --git a/tests/test_modal_finetune_prep.py b/tests/test_modal_finetune_prep.py new file mode 100644 index 0000000000000000000000000000000000000000..684559f145d2dfe54d0730a7e9b3134ee8e04604 --- /dev/null +++ b/tests/test_modal_finetune_prep.py @@ -0,0 +1,201 @@ +import importlib.util +import json +from pathlib import Path + +import pytest + + +def _row(row_id: str, task_type: str, category: str, repair_scope: str | None = None) -> dict: + metadata = {"task_type": task_type} + if repair_scope: + metadata["repair_scope"] = repair_scope + return { + "case_id": row_id, + "uuid": row_id, + "category": category, + "messages": [ + {"role": "user", "content": f"prompt {row_id}"}, + {"role": "assistant", "content": '{"protocol_urgency":"routine"}'}, + ], + "metadata": metadata, + } + + +def _write_jsonl(path: Path, rows: list[dict]) -> None: + path.write_text("".join(json.dumps(row) + "\n" for row in rows), encoding="utf-8") + + +def _load_modal_module(): + module_path = Path(__file__).resolve().parents[1] / "modal" / "finetune_figment_nemotron.py" + spec = importlib.util.spec_from_file_location("figment_modal_finetune", module_path) + assert spec is not None + module = importlib.util.module_from_spec(spec) + assert spec.loader is not None + spec.loader.exec_module(module) + return module + + +def test_prepare_modal_dataset_stratifies_and_preserves_rows(tmp_path): + from scripts.prepare_modal_finetune_dataset import prepare_dataset + + rows = [] + rows.extend(_row(f"full-{index}", "navigator_full", "missing_observation_cues") for index in range(8)) + rows.extend(_row(f"repair-schema-{index}", "focused_repair", "focused_repair:schema", "schema") for index in range(6)) + rows.extend( + _row( + f"repair-sbar-{index}", + "focused_repair", + "focused_repair:handoff_note_sbar", + "handoff_note_sbar", + ) + for index in range(6) + ) + dataset = tmp_path / "input.jsonl" + output_dir = tmp_path / "prepared" + _write_jsonl(dataset, rows) + + manifest = prepare_dataset( + dataset_path=dataset, + output_dir=output_dir, + dataset_version="figment_sft_test", + validation_fraction=0.2, + seed="unit-test", + min_validation_group_size=5, + ) + + train_rows = [json.loads(line) for line in (output_dir / "train.jsonl").read_text().splitlines()] + validation_rows = [json.loads(line) for line in (output_dir / "validation.jsonl").read_text().splitlines()] + train_ids = {row["uuid"] for row in train_rows} + validation_ids = {row["uuid"] for row in validation_rows} + + assert train_ids.isdisjoint(validation_ids) + assert train_ids | validation_ids == {row["uuid"] for row in rows} + assert manifest["row_count"] == 20 + assert manifest["train_count"] + manifest["validation_count"] == 20 + assert manifest["validation_group_counts"]["navigator_full:missing_observation_cues"] >= 1 + assert manifest["validation_group_counts"]["focused_repair:schema"] >= 1 + assert manifest["validation_group_counts"]["focused_repair:handoff_note_sbar"] >= 1 + + +def test_prepare_modal_dataset_rejects_rows_outside_chat_shape(tmp_path): + from scripts.prepare_modal_finetune_dataset import DatasetPrepError + from scripts.prepare_modal_finetune_dataset import prepare_dataset + + dataset = tmp_path / "bad.jsonl" + bad_row = _row("bad-1", "navigator_full", "missing_observation_cues") + bad_row["messages"] = [{"role": "user", "content": "prompt only"}] + _write_jsonl(dataset, [bad_row]) + + with pytest.raises(DatasetPrepError, match="expected user/assistant messages"): + prepare_dataset( + dataset_path=dataset, + output_dir=tmp_path / "prepared", + dataset_version="figment_sft_test", + ) + + +def test_modal_smoke_config_is_small_and_namespaced(): + module = _load_modal_module() + + config = module.build_train_config( + dataset_version="figment_sft_v1", + output_name="unit", + smoke=True, + max_steps=100, + max_seq_length=12288, + ) + paths = module.dataset_volume_paths("figment_sft_v1") + + assert config["max_steps"] == 5 + assert config["max_seq_length"] == 2048 + assert config["output_dir"].endswith("/figment_sft_v1/unit-smoke") + assert paths["train"].endswith("/figment_sft_v1/train.jsonl") + assert paths["validation"].endswith("/figment_sft_v1/validation.jsonl") + + +def test_modal_default_config_matches_first_run_plan(): + module = _load_modal_module() + + config = module.build_train_config(dataset_version="figment_sft_v1", output_name="pilot") + + assert config["learning_rate"] == 1e-4 + assert config["max_steps"] == 40 + assert config["max_seq_length"] == 16384 + assert config["gradient_accumulation_steps"] == 8 + assert config["validation_steps"] == 25 + assert config["save_steps"] == 40 + + +def test_modal_v4_config_can_use_lower_lr_and_lora_controls(): + module = _load_modal_module() + + config = module.build_train_config( + dataset_version="figment_sft_v4", + output_name="figment-sft-v4-lora", + max_steps=900, + learning_rate=2e-5, + lora_r=16, + lora_alpha=32, + lora_dropout=0.05, + gradient_accumulation_steps=8, + validation_steps=50, + save_steps=100, + ) + + assert config["dataset_version"] == "figment_sft_v4" + assert config["learning_rate"] == 2e-5 + assert config["lora_r"] == 16 + assert config["lora_alpha"] == 32 + assert config["lora_dropout"] == 0.05 + assert config["gradient_accumulation_steps"] == 8 + assert config["validation_steps"] == 50 + assert config["save_steps"] == 100 + + +def test_modal_v5_config_can_resume_from_v4_adapter(): + module = _load_modal_module() + + config = module.build_train_config( + dataset_version="figment_sft_v5", + output_name="figment-sft-v5-lora", + resume_adapter_name="figment-sft-v4-lora", + resume_adapter_dataset_version="figment_sft_v4", + ) + + assert config["resume_adapter_name"] == "figment-sft-v4-lora" + assert config["resume_adapter_dataset_version"] == "figment_sft_v4" + assert config["resume_adapter_dir"] == "/checkpoints/figment_sft_v4/figment-sft-v4-lora" + assert config["output_dir"] == "/checkpoints/figment_sft_v5/figment-sft-v5-lora" + + +def test_modal_entrypoint_exposes_v4_training_knobs(): + source = (Path(__file__).resolve().parents[1] / "modal" / "finetune_figment_nemotron.py").read_text( + encoding="utf-8" + ) + + for parameter in ( + "learning_rate", + "lora_r", + "lora_alpha", + "lora_dropout", + "gradient_accumulation_steps", + "validation_steps", + "save_steps", + "resume_adapter_name", + "resume_adapter_dataset_version", + ): + assert f"{parameter}:" in source + assert f"{parameter}={parameter}" in source or f'"{parameter}": {parameter}' in source + + +def test_modal_merge_config_points_at_checkpoint_volume(): + module = _load_modal_module() + + config = module.build_merge_config( + dataset_version="figment_sft_v1", + adapter_name="pilot-20260608", + ) + + assert config["adapter_dir"] == "/checkpoints/figment_sft_v1/pilot-20260608" + assert config["output_dir"] == "/checkpoints/figment_sft_v1/pilot-20260608-merged-bf16" + assert config["output_name"] == "pilot-20260608-merged-bf16" diff --git a/tests/test_submission_claim_audit.py b/tests/test_submission_claim_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..29f060e3a36b1b2c74ced6f367cd2a0900ed5dd9 --- /dev/null +++ b/tests/test_submission_claim_audit.py @@ -0,0 +1,53 @@ +from pathlib import Path + +from scripts import audit_submission_claims + + +def test_current_submission_claims_stay_evidence_gated() -> None: + report = audit_submission_claims.audit_claims() + + assert report["status"] == "passed" + assert report["violations"] == [] + assert report["gate_status"]["off_grid"] is False + assert report["gate_status"]["local_4b"] is False + assert report["gate_status"]["local_asr"] is False + assert report["gate_status"]["backyard_user_use"] is False + + +def test_audit_flags_unproven_off_grid_claim() -> None: + violations = audit_submission_claims.scan_text( + "Figment has achieved Off the Grid and the no-cloud route is proven.", + gate_status={gate.key: False for gate in audit_submission_claims.CLAIM_GATES}, + ) + + assert {violation["gate"] for violation in violations} == {"off_grid"} + assert "recorded no-cloud trace" in violations[0]["required_evidence"] + + +def test_audit_allows_proof_needed_language() -> None: + text = "\n".join( + [ + "Off the Grid is targeted / proof-needed until a recorded no-cloud run exists.", + "Parakeet remains not demo-visible as local ASR proof.", + "Do not say the target user used or tested Figment until factual notes exist.", + ] + ) + + assert audit_submission_claims.scan_text(text) == [] + + +def test_audit_flags_unproven_user_use_and_local_asr_claims() -> None: + text = "\n".join( + [ + "The responder tested Figment and approved it for field documentation.", + "Parakeet ASR is demo-visible and proven for local audio intake.", + ] + ) + violations = audit_submission_claims.scan_text( + text, + relative_path=Path("submission.md"), + gate_status={gate.key: False for gate in audit_submission_claims.CLAIM_GATES}, + ) + + assert [violation["gate"] for violation in violations] == ["backyard_user_use", "local_asr"] + assert {violation["file"] for violation in violations} == {"submission.md"} diff --git a/tests/test_v4_training_seed_export.py b/tests/test_v4_training_seed_export.py new file mode 100644 index 0000000000000000000000000000000000000000..fd3ed2cd8fc278ff02e76c5a70dc9876784f1c0f --- /dev/null +++ b/tests/test_v4_training_seed_export.py @@ -0,0 +1,210 @@ +import json +from pathlib import Path + +from scripts.export_v4_training_seeds import export_v4_training_seeds + + +def _write_jsonl(path: Path, rows: list[dict]) -> None: + path.write_text("".join(json.dumps(row, sort_keys=True) + "\n" for row in rows), encoding="utf-8") + + +def test_exports_failed_holdout_rows_as_non_direct_v4_seeds(tmp_path: Path) -> None: + cases = tmp_path / "field_workflow_holdout_v1.jsonl" + eval_path = tmp_path / "eval.jsonl" + output = tmp_path / "seeds.jsonl" + _write_jsonl( + cases, + [ + { + "case_id": "holdout-1", + "dataset_version": "field_workflow_holdout_v1", + "workflow_category": "radio_handoff", + "structured_intake": {"chief_concern": "radio handoff", "confirmed": True}, + "target_protocol_card_id": "REFERRAL-SBAR-v1", + "expected_red_flag_rule_ids": ["RED-1"], + "expected_min_protocol_urgency": "urgent", + "expected_source_card_ids": ["REFERRAL-SBAR-v1"], + "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], + } + ], + ) + _write_jsonl( + eval_path, + [ + { + "case_id": "holdout-1", + "case_path": str(cases), + "case_line": 1, + "target_protocol_card_id": "REFERRAL-SBAR-v1", + "expected_red_flag_rule_ids": ["RED-1"], + "actual_red_flag_rule_ids": ["RED-1"], + "expected_min_protocol_urgency": "urgent", + "expected_source_card_ids": ["REFERRAL-SBAR-v1"], + "expected_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], + "expected_handoff_cues": ["red flags already fired"], + "actual_protocol_urgency": "urgent", + "actual_source_card_ids": ["REFERRAL-SBAR-v1"], + "actual_candidate_pathway_card_ids": ["REFERRAL-SBAR-v1"], + "final_validation": {"passed": True, "failures": []}, + "final_output": { + "protocol_urgency": "urgent", + "source_cards": ["REFERRAL-SBAR-v1"], + "candidate_protocol_pathways": [{"card_id": "REFERRAL-SBAR-v1"}], + "missing_info_to_collect": [], + "next_observations_to_collect": [], + "handoff_note_sbar": { + "situation": "Needs handoff.", + "background": "Known background.", + "assessment_observations_only": "Observed concern.", + "handoff_request": "Request review.", + }, + }, + } + ], + ) + + manifest = export_v4_training_seeds(eval_path=eval_path, output_path=output) + seeds = [json.loads(line) for line in output.read_text(encoding="utf-8").splitlines()] + + assert manifest["seed_count"] == 1 + assert seeds[0]["seed_type"] == "v4_failure_seed" + assert seeds[0]["direct_training_allowed"] is False + assert seeds[0]["repair_scopes"] == ["handoff_note_sbar"] + assert seeds[0]["structured_intake"]["chief_concern"] == "radio handoff" + assert "Do not copy" in seeds[0]["teacher_instruction"] + + +def test_can_export_high_quality_replay_candidates_when_requested(tmp_path: Path) -> None: + cases = tmp_path / "cases.jsonl" + eval_path = tmp_path / "eval.jsonl" + output = tmp_path / "seeds.jsonl" + _write_jsonl( + cases, + [ + { + "case_id": "case-1", + "dataset_version": "figment_sft_v3", + "structured_intake": {"chief_concern": "wound", "confirmed": True}, + "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", + } + ], + ) + _write_jsonl( + eval_path, + [ + { + "case_id": "case-1", + "case_path": str(cases), + "case_line": 1, + "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", + "expected_min_protocol_urgency": "urgent", + "expected_red_flag_rule_ids": [], + "actual_red_flag_rule_ids": [], + "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], + "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], + "actual_protocol_urgency": "urgent", + "actual_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], + "actual_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], + "final_validation": {"passed": True, "failures": []}, + "final_output": { + "protocol_urgency": "urgent", + "source_cards": ["WOUND-INFECTION-ESCALATION-v1"], + "candidate_protocol_pathways": [{"card_id": "WOUND-INFECTION-ESCALATION-v1"}], + "missing_info_to_collect": [], + "next_observations_to_collect": [], + "handoff_note_sbar": { + "situation": "Wound concern.", + "background": "Known background.", + "assessment_observations_only": "Observed wound concern.", + "handoff_request": "Request review.", + }, + }, + } + ], + ) + + manifest = export_v4_training_seeds(eval_path=eval_path, output_path=output, include_passing=True) + seeds = [json.loads(line) for line in output.read_text(encoding="utf-8").splitlines()] + + assert manifest["replay_seed_count"] == 1 + assert seeds[0]["seed_type"] == "v4_replay_candidate" + assert seeds[0]["direct_training_allowed"] is True + + +def test_harness_only_evidence_miss_is_not_a_model_failure_seed(tmp_path: Path) -> None: + cases = tmp_path / "field_workflow_holdout_v1.jsonl" + eval_path = tmp_path / "eval.jsonl" + output = tmp_path / "seeds.jsonl" + _write_jsonl( + cases, + [ + { + "case_id": "holdout-2", + "dataset_version": "field_workflow_holdout_v1", + "workflow_category": "rural_clinic_intake", + "structured_intake": { + "chief_concern": "wound check", + "confirmed": True, + "workflow_category": "rural_clinic_intake", + }, + "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", + "expected_red_flag_rule_ids": [], + "expected_min_protocol_urgency": "urgent", + "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], + "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], + "expected_missing_observations": [ + "wound redness or swelling extent", + "manual correction status for audio-derived fields", + ], + } + ], + ) + _write_jsonl( + eval_path, + [ + { + "case_id": "holdout-2", + "case_path": str(cases), + "case_line": 1, + "target_protocol_card_id": "WOUND-INFECTION-ESCALATION-v1", + "expected_red_flag_rule_ids": [], + "actual_red_flag_rule_ids": [], + "expected_min_protocol_urgency": "urgent", + "expected_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], + "expected_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], + "expected_missing_observations": [ + "wound redness or swelling extent", + "manual correction status for audio-derived fields", + ], + "actual_protocol_urgency": "urgent", + "actual_source_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], + "actual_candidate_pathway_card_ids": ["WOUND-INFECTION-ESCALATION-v1"], + "final_validation": {"passed": True, "failures": []}, + "final_output": { + "protocol_urgency": "urgent", + "source_cards": ["WOUND-INFECTION-ESCALATION-v1"], + "candidate_protocol_pathways": [{"card_id": "WOUND-INFECTION-ESCALATION-v1"}], + "missing_info_to_collect": ["wound redness or swelling extent"], + "next_observations_to_collect": ["wound redness or swelling extent"], + "handoff_note_sbar": { + "situation": "Wound concern.", + "background": "Known background.", + "assessment_observations_only": "Observed wound concern.", + "handoff_request": "Request review.", + }, + }, + } + ], + ) + + manifest = export_v4_training_seeds(eval_path=eval_path, output_path=output, include_passing=True) + seeds = [json.loads(line) for line in output.read_text(encoding="utf-8").splitlines()] + + assert manifest["failure_seed_count"] == 0 + assert manifest["replay_seed_count"] == 1 + assert manifest["harness_only_score_failure_count"] == 1 + assert seeds[0]["seed_type"] == "v4_replay_candidate" + assert seeds[0]["model_training_failed"] is False + assert seeds[0]["harness_only_score_failure"] is True + assert seeds[0]["repair_scopes"] == [] + assert seeds[0]["workflow_category"] == "rural_clinic_intake" diff --git a/tests/test_v6_replay_selection.py b/tests/test_v6_replay_selection.py new file mode 100644 index 0000000000000000000000000000000000000000..d95f68f3f4a5800af82ea9bf75ecf8755192387f --- /dev/null +++ b/tests/test_v6_replay_selection.py @@ -0,0 +1,147 @@ +import json +from pathlib import Path + + +def _row( + *, + case_id: str = "case-1", + category: str = "focused_repair:handoff_note_sbar", + output: dict | None = None, + dataset_version: str = "figment_sft_v5", + metadata: dict | None = None, +) -> dict: + assistant_output = output or { + "handoff_note_sbar": { + "situation": "confirmed field handoff", + "background": "low-resource setting", + "assessment_observations_only": "observations only", + "handoff_request": "request protocol review", + } + } + merged_metadata = { + "dataset_version": dataset_version, + "task_type": "focused_repair" if "protocol_urgency" not in assistant_output else "navigator_full", + "validator_passed": True, + "validation_result": {"passed": True, "failures": []}, + "expected_label_score": { + "all_expected_labels_passed": True, + "forbidden_behavior_absent": True, + }, + } + if metadata: + merged_metadata.update(metadata) + return { + "case_id": case_id, + "category": category, + "version": dataset_version, + "metadata": merged_metadata, + "messages": [ + {"role": "user", "content": "prompt"}, + {"role": "assistant", "content": json.dumps(assistant_output, sort_keys=True)}, + ], + } + + +def test_v6_replay_audit_rejects_duplicate_long_observation_lists(): + from scripts.build_v6_replay_corpus import audit_row + + row = _row( + output={ + "protocol_urgency": "urgent", + "missing_info_to_collect": ["a", "b", "c", "d"], + "next_observations_to_collect": ["a", "b", "c", "d"], + }, + category="sbar_observation_ownership", + ) + + result = audit_row(row) + + assert result.accepted is False + assert "duplicate_long_missing_and_next_observations" in result.reasons + + +def test_v6_replay_audit_rejects_harness_metadata_in_observation_fields(): + from scripts.build_v6_replay_corpus import audit_row + + row = _row( + output={ + "protocol_urgency": "urgent", + "missing_info_to_collect": ["retrieve source protocol card IDs"], + "next_observations_to_collect": ["count respiratory rate"], + }, + category="general_regression", + ) + + result = audit_row(row) + + assert result.accepted is False + assert "harness_metadata_observation:source_protocol_card_ids" in result.reasons + + +def test_v6_replay_audit_requires_selected_ids_for_observation_focused_full_rows(): + from scripts.build_v6_replay_corpus import audit_row + + row = _row( + output={ + "protocol_urgency": "urgent", + "missing_info_to_collect": ["count respiratory rate"], + "next_observations_to_collect": ["count respiratory rate"], + }, + category="required_observation_id_selection", + ) + + result = audit_row(row) + + assert result.accepted is False + assert "observation_focused_row_missing_selected_required_observation_ids" in result.reasons + + +def test_v6_replay_audit_accepts_clean_non_observation_repair_row(): + from scripts.build_v6_replay_corpus import audit_row + + result = audit_row(_row()) + + assert result.accepted is True + assert result.reasons == () + + +def test_build_v6_replay_corpus_writes_only_clean_rows(tmp_path: Path): + from scripts.build_v6_replay_corpus import build_replay_corpus + + input_path = tmp_path / "rows.jsonl" + clean = _row(case_id="clean") + bad = _row( + case_id="bad", + output={ + "protocol_urgency": "urgent", + "missing_info_to_collect": ["source protocol card IDs"], + "next_observations_to_collect": ["source protocol card IDs"], + }, + category="general_regression", + ) + input_path.write_text( + json.dumps(clean, sort_keys=True) + "\n" + json.dumps(bad, sort_keys=True) + "\n", + encoding="utf-8", + ) + output_path = tmp_path / "selected.jsonl" + manifest_path = tmp_path / "manifest.json" + + summary = build_replay_corpus( + input_paths=[input_path], + output_path=output_path, + manifest_path=manifest_path, + targets={"figment_sft_v5": 2}, + seed="test", + ) + + selected_rows = [json.loads(line) for line in output_path.read_text(encoding="utf-8").splitlines()] + + assert summary["selected_rows"] == 1 + assert len(selected_rows) == 1 + assert selected_rows[0]["case_id"] == "clean" + assert selected_rows[0]["metadata"]["v6_replay_audit"]["accepted"] is True + assert summary["shortage_by_source_dataset_version"] == {"figment_sft_v5": 1} + assert summary["rejected_reason_counts"] == { + "figment_sft_v5:harness_metadata_observation:source_protocol_card_ids": 1 + } +