Publish record-level V19 bbb_martins

README.md

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+---
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: train/data.parquet
+  - split: validation_ranking
+    path: validation_ranking/data.parquet
+  - split: test_ranking
+    path: test_ranking/data.parquet
+---
+# BBB_Martins record-level transfer V19
+
+This indirect-only dataset retains individual eligible numeric records from exact Stage-3 assay
+buckets with at least 20 proper-train parents. Each prompt shows A's and B's own assay details;
+only A shows measurement and result-bearing evidence. Validation is held out from source train;
+test uses the selected-gold validation scaffold universe. Rankings use 20 Morgan-nearest train
+parents.
+
+- train rows: 171,363
+- validation ranking rows: 3,800
+- test ranking rows: 2,460
+- target: train-SD sigmoid, center 0.4 SD, temperature 0.10
+- training references: up to 24, balanced around 0.4 SD

manifest.json

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+{
+  "arrow_schema": "prompt: string\ncompletion: string\nsplit: string\npair_id: string\nranking_query_id: string\nranking_member_index: int64\nranking_candidate_row_count: int64\nranking_candidate_parent_count: int64\nretrieval_parent_rank: int64\nretrieval_parent_context_index: int64\nretrieval_parent_context_count: int64\ntask_id: string\nsource_id: string\nretrieval_strategy: string\nquery_record_id: string\nretrieval_record_id: string\nquery_benchmark_row_id: string\nretrieval_benchmark_row_id: string\nquery_molecule_identity_key: string\nretrieval_molecule_identity_key: string\nquery_smiles: string\nretrieval_smiles: string\nquery_condition_group: string\nretrieval_condition_group: string\nquery_condition_scope: string\nretrieval_condition_scope: string\nquery_condition_atoms: list<element: string>\n  child 0, element: string\nretrieval_condition_atoms: list<element: string>\n  child 0, element: string\ncandidate_context_relation: string\nquery_source_record_count: int64\nretrieval_source_record_count: int64\nquery_agreement_fraction: double\nretrieval_agreement_fraction: double\nquery_gold_Y: int64\nretrieval_gold_Y: int64\nranking_balance_label: string\nquery_geometry_value: double\nretrieval_geometry_value: double\nabsolute_geometry_difference: double\ncalibration_sample_standard_deviation: double\ntarget_distribution: struct<nontransfer: double, transfer: double>\n  child 0, nontransfer: double\n  child 1, transfer: double\ncanonical_endpoint_key: string\nassay_concept: string\nmeasurement_kind: string\nmetadata: struct<calibration_sha256: string, groups: struct<assay_concept: string, measurement_kind: string, q (... 230 chars omitted)\n  child 0, calibration_sha256: string\n  child 1, groups: struct<assay_concept: string, measurement_kind: string, query_condition_group: string, query_conditi (... 81 chars omitted)\n      child 0, assay_concept: string\n      child 1, measurement_kind: string\n      child 2, query_condition_group: string\n      child 3, query_condition_scope: string\n      child 4, retrieval_strategy: string\n      child 5, source_id: string\n      child 6, task_id: string\n  child 2, soft_targets: struct<(A): double, (B): double>\n      child 0, (A): double\n      child 1, (B): double\n  child 3, source_snapshot_sha256: string\n  child 4, target_contract: string\nabsolute_canonical_value_difference: double\nstandardized_canonical_value_difference: double\nsd_logistic_similarity: double\ntarget_train_sample_standard_deviation: double\ntarget_a: double\ntarget_b: double\nlabel_mode: string\nbinary_label: int64\nis_decisive: bool\nmorgan_tanimoto_similarity: double\ngraph_a_position: int64\ngraph_b_position: int64\ngraph_offset: int64\nrepresentation: string\npair_bucket_key: string\nquery_parent_id: string\nretrieval_parent_id: string\nquery_scaffold: string\nretrieval_scaffold: string\nquery_evidence: struct<aggregation_method: string, display_measurement_text: string, display_unit_text: string, disp (... 184 chars omitted)\n  child 0, aggregation_method: string\n  child 1, display_measurement_text: string\n  child 2, display_unit_text: string\n  child 3, display_transform_id: string\n  child 4, source_record_count: int64\n  child 5, deduplicated_source_record_count: int64\n  child 6, aggregate_min: double\n  child 7, aggregate_max: double\n  child 8, aggregate_q1: double\n  child 9, aggregate_q3: double\nretrieval_evidence: struct<aggregation_method: string, display_measurement_text: string, display_unit_text: string, disp (... 184 chars omitted)\n  child 0, aggregation_method: string\n  child 1, display_measurement_text: string\n  child 2, display_unit_text: string\n  child 3, display_transform_id: string\n  child 4, source_record_count: int64\n  child 5, deduplicated_source_record_count: int64\n  child 6, aggregate_min: double\n  child 7, aggregate_max: double\n  child 8, aggregate_q1: double\n  child 9, aggregate_q3: double",
+  "artifacts": {
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+    "calibration.json": "a2eb2268166dcfe57fa234ef295ddf4719509a8d5724479cbcebc44f4b0d5c6b",
+    "test_ranking/data.parquet": "9f0314cfc056be19549fb8c3ffa59a5674efa08051a687427cdfd8929c2deca2",
+    "train/data.parquet": "b3652c50e522e35cf4308c831a29e41039c1985ed31c5de0d18229eaaeaa50c5",
+    "validation_ranking/data.parquet": "437cf943b620c58c7339943b1749a19bca5b28b10a70be4c55ead391b4a1bc6e"
+  },
+  "build": {
+    "implementation_sha256": {
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+      "assay_transfer/record_level/v19/contract.py": "edfbe0d0c0b0618f549aea248141624b2efaefc6bc27228e9a63fbee2b316dc8",
+      "assay_transfer/record_level/v19/hf.py": "937e735cde268725a9ebf1d0a429808d296121ef4428663b33523570410980a0",
+      "assay_transfer/record_level/v19/pairs.py": "168f6028e450000fc5aaf9264cc8a4b4646e43ef3c7e492c374d64b550f71d04",
+      "assay_transfer/record_level/v19/projection.py": "ab771bab1be25906eb002bfb1a225abdfbbc8be206bce11863e20afc764813b8",
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+      "assay_transfer/record_level/v19/prompt_projection.json": "f7216b879d68182e3d94221312ea669f973f2ff95c643ab1011c1bd0cdd27311",
+      "assay_transfer/record_level/v19/publish.py": "f1b96094c76d6c428233ed8371b199658f484176dc5846d300e0dc530e9475f5",
+      "assay_transfer/record_level/v19/splits.py": "1cb93ec1bcbb0f22a0d66bdad865c9958b047290517ccedb02b31983b192bff0"
+    },
+    "packages": {
+      "duckdb": "1.5.3",
+      "huggingface_hub": "0.36.2",
+      "jinja2": "3.1.6",
+      "pyarrow": "23.0.0",
+      "rdkit": "2025.9.4"
+    },
+    "python": "3.11.14",
+    "ranking_cap": 20,
+    "reference_cap": 24,
+    "repository_commit": "7ae235a1573a01dc281266ff781bda01e80d8ae0",
+    "repository_dirty": true,
+    "training_reference_caps": {}
+  },
+  "calibration_sha256": "a2eb2268166dcfe57fa234ef295ddf4719509a8d5724479cbcebc44f4b0d5c6b",
+  "hub_dataset_id": "jiosephlee/assay-transfer-record-level-v19-bbb-martins-numeric-intern",
+  "label_mode": "numeric_record_level_only",
+  "membership": {
+    "test_ranking": {
+      "pair_artifact_sha256": "3d846dd337c46cd0ec1c9c0701f513a8ba0d16d1c1940982e1fbdb56eb406039"
+    },
+    "train": {
+      "pair_artifact_sha256": "1cd7f9056cb53c958015e3f39e5b0c21b9e708d462ee77cedd4626fc008cca64"
+    },
+    "validation_ranking": {
+      "pair_artifact_sha256": "89395420c8dd59866f8386df623813a0cbae9220ac2b2e41603edfb3471ff7df"
+    }
+  },
+  "pair_manifest_sha256": "aa6ef782e186ee0ab197e81f75e727cd2143c63e442d23c1cb9246e9b89d8e2d",
+  "prompt_contract": {
+    "known_measurement": "A_only",
+    "projection_sha256": "f7216b879d68182e3d94221312ea669f973f2ff95c643ab1011c1bd0cdd27311",
+    "query_result_bearing_fields": "hidden",
+    "record_context": "separate_A_and_B",
+    "template": "prompt.jinja",
+    "template_sha256": "66490ddc0070232519289f03bc3342e32af67af67b81b91f32744222be9a37e1"
+  },
+  "rows": {
+    "test_ranking": 2460,
+    "train": 171363,
+    "validation_ranking": 3800
+  },
+  "schema_version": "assay_transfer_numeric_record_level.v19",
+  "split_manifest_sha256": "ac099ee89d14b34a7be826e1b6e1387a43eb970d775e3ec9e8cbd76b00ebabb8",
+  "stage": "hf",
+  "target_contract": "train_sd_sigmoid_center_0.4_temperature_0.1_unclipped.record_level_v19",
+  "task_id": "bbb_martins",
+  "version": "v19"
+}

test_ranking/data.parquet

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train/data.parquet

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validation_ranking/data.parquet

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