diff --git a/TASK_METHOD_20_GAP_AUDIT.md b/TASK_METHOD_20_GAP_AUDIT.md
index 3a11048c4167d3fe4171551efe833e2ce3c27498..8ff686bca88288160c59858b240bcb7c362add61 100644
--- a/TASK_METHOD_20_GAP_AUDIT.md
+++ b/TASK_METHOD_20_GAP_AUDIT.md
@@ -1,6 +1,6 @@
 # Task Method 20-Result Gap Audit
 
-Generated: `2026-06-16T15:06:55+00:00`
+Generated: `2026-06-17T07:04:39+00:00`
 
 This audit is the explicit gap ledger for the 9-method x 20-task result matrix.
 It keeps missing cells visible while preserving the rule that a numeric score
@@ -9,8 +9,8 @@ requires a real task target and source artifact.
 ## Score Summary
 
 - Method-task records: `180`
-- Numeric scored records: `113`
-- Scoreless records: `67`
+- Numeric scored records: `116`
+- Scoreless records: `64`
 - Proxy-scored records: `4`
 - Source matrix: [`docs/data/task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json)
 
@@ -24,7 +24,7 @@ requires a real task target and source artifact.
 | 128ep Metadata NN | metadata128_neural_mlp | 6/20 | 14 | 0 | not_supported_by_metadata_only_package: 14, scored: 6 |
 | 128ep Raw Simple | raw128_simple | 20/20 | 0 | 2 | proxy_scored: 2, scored: 18 |
 | 128ep Raw NN | raw128_neural_mlp | 20/20 | 0 | 2 | proxy_scored: 2, scored: 18 |
-| Qwen3-Omni v6 LoRA | qwen3_omni_v6_lora | 7/20 | 13 | 0 | not_evaluated_in_verified_package: 13, scored: 7 |
+| Qwen3-Omni v6 LoRA | qwen3_omni_v6_lora | 10/20 | 10 | 0 | not_evaluated_in_verified_package: 10, scored: 10 |
 | Cosmos3-Super Reasoner | cosmos3_super_reasoner | 7/20 | 13 | 0 | not_evaluated_in_verified_package: 13, scored: 7 |
 | Cosmos3-Nano Future Window | cosmos3_nano_future_window | 5/20 | 15 | 0 | not_evaluated_in_verified_package: 15, scored: 5 |
 
@@ -32,7 +32,7 @@ requires a real task target and source artifact.
 
 | Status | Count | Next step |
 | --- | --- | --- |
-| not_evaluated_in_verified_package | 41 | Generate verified model outputs for this task contract and score them against the held-out labels. |
+| not_evaluated_in_verified_package | 38 | Generate verified model outputs for this task contract and score them against the held-out labels. |
 | not_supported_by_metadata_only_package | 22 | Run the task with raw sensor-feature blocks or add a task-specific metadata target builder before assigning a numeric score. |
 | unsupported_without_required_target | 4 | Export the missing target field for this 128-episode method, then rerun the same train/validation/test split. |
 
@@ -71,12 +71,10 @@ requires a real task target and source artifact.
 | 12 | Multimodal Synchronization Detection | Cosmos3-Nano Future Window | not evaluated | Generate verified model outputs for this task contract and score them against the held-out labels. |
 | 13 | Long-Horizon Next-Action Forecasting | 128ep Metadata Simple | not supported | Run the task with raw sensor-feature blocks or add a task-specific metadata target builder before assigning a numeric score. |
 | 13 | Long-Horizon Next-Action Forecasting | 128ep Metadata NN | not supported | Run the task with raw sensor-feature blocks or add a task-specific metadata target builder before assigning a numeric score. |
-| 13 | Long-Horizon Next-Action Forecasting | Qwen3-Omni v6 LoRA | not evaluated | Generate verified model outputs for this task contract and score them against the held-out labels. |
 | 13 | Long-Horizon Next-Action Forecasting | Cosmos3-Super Reasoner | not evaluated | Generate verified model outputs for this task contract and score them against the held-out labels. |
 | 13 | Long-Horizon Next-Action Forecasting | Cosmos3-Nano Future Window | not evaluated | Generate verified model outputs for this task contract and score them against the held-out labels. |
 | 14 | Long-Horizon Next-Subtask Forecasting | 128ep Metadata Simple | not supported | Run the task with raw sensor-feature blocks or add a task-specific metadata target builder before assigning a numeric score. |
 | 14 | Long-Horizon Next-Subtask Forecasting | 128ep Metadata NN | not supported | Run the task with raw sensor-feature blocks or add a task-specific metadata target builder before assigning a numeric score. |
-| 14 | Long-Horizon Next-Subtask Forecasting | Qwen3-Omni v6 LoRA | not evaluated | Generate verified model outputs for this task contract and score them against the held-out labels. |
 | 14 | Long-Horizon Next-Subtask Forecasting | Cosmos3-Super Reasoner | not evaluated | Generate verified model outputs for this task contract and score them against the held-out labels. |
 | 14 | Long-Horizon Next-Subtask Forecasting | Cosmos3-Nano Future Window | not evaluated | Generate verified model outputs for this task contract and score them against the held-out labels. |
 | 15 | Interaction Text Prediction | 128ep Metadata Simple | not supported | Run the task with raw sensor-feature blocks or add a task-specific metadata target builder before assigning a numeric score. |
@@ -89,7 +87,6 @@ requires a real task target and source artifact.
 | 16 | Action-Object Relation Prediction | Cosmos3-Nano Future Window | not evaluated | Generate verified model outputs for this task contract and score them against the held-out labels. |
 | 17 | Future Object-Set Forecasting | 128ep Metadata Simple | not supported | Run the task with raw sensor-feature blocks or add a task-specific metadata target builder before assigning a numeric score. |
 | 17 | Future Object-Set Forecasting | 128ep Metadata NN | not supported | Run the task with raw sensor-feature blocks or add a task-specific metadata target builder before assigning a numeric score. |
-| 17 | Future Object-Set Forecasting | Qwen3-Omni v6 LoRA | not evaluated | Generate verified model outputs for this task contract and score them against the held-out labels. |
 | 17 | Future Object-Set Forecasting | Cosmos3-Super Reasoner | not evaluated | Generate verified model outputs for this task contract and score them against the held-out labels. |
 | 17 | Future Object-Set Forecasting | Cosmos3-Nano Future Window | not evaluated | Generate verified model outputs for this task contract and score them against the held-out labels. |
 | 18 | IMU-to-Hand Pose Reconstruction | 128ep Metadata Simple | not supported | Run the task with raw sensor-feature blocks or add a task-specific metadata target builder before assigning a numeric score. |
diff --git a/TASK_METHOD_20_RESULT_MATRIX.md b/TASK_METHOD_20_RESULT_MATRIX.md
index 782f017deedfda9593460a4ca271f4bedb6220af..922a83af942107af3c2dc87b52ed394ab40406c6 100644
--- a/TASK_METHOD_20_RESULT_MATRIX.md
+++ b/TASK_METHOD_20_RESULT_MATRIX.md
@@ -12,7 +12,7 @@ Legend: `score` = numeric task score, `proxy` = documented raw128 compact proxy
 | 128ep Metadata NN | 20 | 6 | 0 | 14 | not supported 14, scored 6 |
 | 128ep Raw Simple | 20 | 20 | 2 | 0 | proxy scored 2, scored 18 |
 | 128ep Raw NN | 20 | 20 | 2 | 0 | proxy scored 2, scored 18 |
-| Qwen3-Omni v6 LoRA | 20 | 7 | 0 | 13 | not evaluated 13, scored 7 |
+| Qwen3-Omni v6 LoRA | 20 | 10 | 0 | 10 | not evaluated 10, scored 10 |
 | Cosmos3-Super Reasoner | 20 | 7 | 0 | 13 | not evaluated 13, scored 7 |
 | Cosmos3-Nano Future Window | 20 | 5 | 0 | 15 | not evaluated 15, scored 5 |
 
@@ -30,11 +30,11 @@ Legend: `score` = numeric task score, `proxy` = documented raw128 compact proxy
 | 10 | Cross-Modal Reconstruction | score | score | unsupported | not supported | score | score | not evaluated | not evaluated | not evaluated |
 | 11 | Temporal Order Verification | score | score | score | not supported | score | score | not evaluated | not evaluated | not evaluated |
 | 12 | Multimodal Synchronization Detection | score | score | unsupported | not supported | score | score | not evaluated | not evaluated | not evaluated |
-| 13 | Long-Horizon Next-Action Forecasting | score | score | not supported | not supported | score | score | not evaluated | not evaluated | not evaluated |
-| 14 | Long-Horizon Next-Subtask Forecasting | score | score | not supported | not supported | score | score | not evaluated | not evaluated | not evaluated |
+| 13 | Long-Horizon Next-Action Forecasting | score | score | not supported | not supported | score | score | score | not evaluated | not evaluated |
+| 14 | Long-Horizon Next-Subtask Forecasting | score | score | not supported | not supported | score | score | score | not evaluated | not evaluated |
 | 15 | Interaction Text Prediction | score | score | not supported | not supported | proxy | proxy | not evaluated | not evaluated | not evaluated |
 | 16 | Action-Object Relation Prediction | score | score | not supported | not supported | score | score | score | score | not evaluated |
-| 17 | Future Object-Set Forecasting | score | score | not supported | not supported | score | score | not evaluated | not evaluated | not evaluated |
+| 17 | Future Object-Set Forecasting | score | score | not supported | not supported | score | score | score | not evaluated | not evaluated |
 | 18 | IMU-to-Hand Pose Reconstruction | score | score | not supported | not supported | score | score | not evaluated | not evaluated | not evaluated |
 | 19 | Camera-View Synchronization Retrieval | score | score | not supported | not supported | proxy | proxy | not evaluated | not evaluated | not evaluated |
 | 20 | Time-to-Next-Transition Regression | score | score | not supported | not supported | score | score | not evaluated | not evaluated | not evaluated |
diff --git a/assets/charts/episode128_task_model_radar.svg b/assets/charts/episode128_task_model_radar.svg
index bd5d9c6b5203aba2d2bcc52bfcebbb0775a57f96..5aa6f68fc03b7e6e51ee53e3d5cde00127dcb13d 100644
--- a/assets/charts/episode128_task_model_radar.svg
+++ b/assets/charts/episode128_task_model_radar.svg
@@ -14,11 +14,11 @@
 <rect x="250" y="174" width="250" height="34" rx="17" fill="#67e8d1" fill-opacity="0.10" stroke="#67e8d1" stroke-opacity="0.38"/>
 <text x="266.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#67e8d1" opacity="1.000">140 method-task records</text>
 <rect x="512" y="174" width="168" height="34" rx="17" fill="#22d3ee" fill-opacity="0.10" stroke="#22d3ee" stroke-opacity="0.38"/>
-<text x="528.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#22d3ee" opacity="1.000">73 scored axes</text>
+<text x="528.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#22d3ee" opacity="1.000">76 scored axes</text>
 <rect x="692" y="174" width="250" height="34" rx="17" fill="#f59e0b" fill-opacity="0.10" stroke="#f59e0b" stroke-opacity="0.38"/>
 <text x="708.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#f59e0b" opacity="1.000">40/40 raw128 pass</text>
 <rect x="954" y="174" width="250" height="34" rx="17" fill="#f472b6" fill-opacity="0.10" stroke="#f472b6" stroke-opacity="0.38"/>
-<text x="970.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#f472b6" opacity="1.000">67 explicit scoreless</text>
+<text x="970.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#f472b6" opacity="1.000">64 explicit scoreless</text>
 <rect x="54" y="235" width="1190" height="1190" rx="14" fill="#020502" fill-opacity="0.42" stroke="#ccffa0" stroke-opacity="0.14"/>
 <text x="84.0" y="276.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="23" font-weight="800" fill="#f4f8ef" opacity="1.000">Normalized task scores</text>
 <text x="84.0" y="302.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="560" fill="#a5afa2" opacity="1.000">Each axis is one task. Longer radius means better after metric-direction normalization.</text>
@@ -154,7 +154,10 @@
 <circle cx="662.4" cy="851.0" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
 <circle cx="940.3" cy="860.0" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
 <circle cx="753.5" cy="893.6" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
+<circle cx="649.5" cy="860.7" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
+<circle cx="648.8" cy="860.9" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
 <circle cx="649.9" cy="860.0" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
+<circle cx="594.0" cy="841.8" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
 <circle cx="650.0" cy="859.7" r="8.0" fill="#ff9c7a" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
 <circle cx="650.0" cy="860.0" r="8.0" fill="#ff9c7a" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
 <circle cx="726.9" cy="754.2" r="8.0" fill="#ff9c7a" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
@@ -191,7 +194,7 @@
 <line x1="1315" y1="445" x2="1365" y2="445" stroke="#9bb8ff" stroke-width="7" stroke-linecap="round"/>
 <circle cx="1340" cy="445" r="7" fill="#9bb8ff" stroke="#020502" stroke-width="2"/>
 <text x="1381.0" y="440.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="15" font-weight="800" fill="#f4f8ef" opacity="1.000">Qwen3-Omni v6 LoRA</text>
-<text x="1707.0" y="440.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="800" fill="#9bb8ff" opacity="1.000">20 records / 7 scored</text>
+<text x="1707.0" y="440.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="800" fill="#9bb8ff" opacity="1.000">20 records / 10 scored</text>
 <text x="1381.0" y="460.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="11" font-weight="560" fill="#a5afa2" opacity="1.000">Verified held-out Qwen3-Omni v6 LoRA metrics, plus task 16 and any completed</text>
 <text x="1381.0" y="475.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="11" font-weight="560" fill="#a5afa2" opacity="1.000">private-GPU future-task probes scored from task-specific JSON.</text>
 <line x1="1315" y1="495" x2="1365" y2="495" stroke="#ff9c7a" stroke-width="7" stroke-linecap="round"/>
diff --git a/assets/charts/unified_task_model_radar.svg b/assets/charts/unified_task_model_radar.svg
index 1fa940ab3d84394401ed0e3d7610fa06276c91bb..bee5d79b236efbdf0172b39c12406aca81fd5ab5 100644
--- a/assets/charts/unified_task_model_radar.svg
+++ b/assets/charts/unified_task_model_radar.svg
@@ -14,7 +14,7 @@
 <rect x="250" y="174" width="250" height="34" rx="17" fill="#67e8d1" fill-opacity="0.10" stroke="#67e8d1" stroke-opacity="0.38"/>
 <text x="266.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#67e8d1" opacity="1.000">180 method-task records</text>
 <rect x="512" y="174" width="250" height="34" rx="17" fill="#22d3ee" fill-opacity="0.10" stroke="#22d3ee" stroke-opacity="0.38"/>
-<text x="528.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#22d3ee" opacity="1.000">113 scored axes</text>
+<text x="528.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#22d3ee" opacity="1.000">116 scored axes</text>
 <rect x="774" y="174" width="250" height="34" rx="17" fill="#f59e0b" fill-opacity="0.10" stroke="#f59e0b" stroke-opacity="0.38"/>
 <text x="790.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#f59e0b" opacity="1.000">40/40 raw128 pass</text>
 <rect x="1036" y="174" width="250" height="34" rx="17" fill="#f472b6" fill-opacity="0.10" stroke="#f472b6" stroke-opacity="0.38"/>
@@ -194,7 +194,10 @@
 <circle cx="662.4" cy="851.0" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
 <circle cx="940.3" cy="860.0" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
 <circle cx="753.5" cy="893.6" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
+<circle cx="649.5" cy="860.7" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
+<circle cx="648.8" cy="860.9" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
 <circle cx="649.9" cy="860.0" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
+<circle cx="594.0" cy="841.8" r="8.0" fill="#9bb8ff" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
 <circle cx="650.0" cy="859.7" r="8.0" fill="#ff9c7a" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
 <circle cx="650.0" cy="860.0" r="8.0" fill="#ff9c7a" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
 <circle cx="726.9" cy="754.2" r="8.0" fill="#ff9c7a" fill-opacity="0.92" stroke="#020502" stroke-width="2.0"/>
@@ -241,7 +244,7 @@
 <line x1="1315" y1="545" x2="1365" y2="545" stroke="#9bb8ff" stroke-width="7" stroke-linecap="round"/>
 <circle cx="1340" cy="545" r="7" fill="#9bb8ff" stroke="#020502" stroke-width="2"/>
 <text x="1381.0" y="540.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="15" font-weight="800" fill="#f4f8ef" opacity="1.000">Qwen3-Omni v6 LoRA</text>
-<text x="1707.0" y="540.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="800" fill="#9bb8ff" opacity="1.000">20 records / 7 scored</text>
+<text x="1707.0" y="540.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="800" fill="#9bb8ff" opacity="1.000">20 records / 10 scored</text>
 <text x="1381.0" y="560.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="11" font-weight="560" fill="#a5afa2" opacity="1.000">Verified held-out Qwen3-Omni v6 LoRA metrics, plus task 16 and any completed</text>
 <text x="1381.0" y="575.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="11" font-weight="560" fill="#a5afa2" opacity="1.000">private-GPU future-task probes scored from task-specific JSON.</text>
 <line x1="1315" y1="595" x2="1365" y2="595" stroke="#ff9c7a" stroke-width="7" stroke-linecap="round"/>
diff --git a/data/artifact_index.json b/data/artifact_index.json
index 8b1986bd191650b42955308376e4e72e3bb00716..391bb70cc5215ef4b9babe10694cbb7183894969 100644
--- a/data/artifact_index.json
+++ b/data/artifact_index.json
@@ -1,13 +1,13 @@
 {
   "title": "Ropedia Xperience-10M Task Suite Artifact Index",
-  "generated_at_utc": "2026-06-16T15:06:56+00:00",
+  "generated_at_utc": "2026-06-17T07:20:47+00:00",
   "status": "pass",
-  "artifact_count": 191,
+  "artifact_count": 199,
   "missing": [],
   "by_kind": {
     "project_path": 14,
     "scaleup_contract": 7,
-    "scaleup_status": 42,
+    "scaleup_status": 44,
     "publication_workflow": 6,
     "reproducibility": 4,
     "project_scope": 1,
@@ -16,9 +16,9 @@
     "website_data": 10,
     "generated_figure": 7,
     "visualization_builder": 1,
-    "model_result": 3,
+    "model_result": 4,
     "result_interpretation": 5,
-    "metrics_source": 27,
+    "metrics_source": 31,
     "visual_evidence": 7,
     "dataset_context": 1,
     "quality_gate": 12,
@@ -35,7 +35,7 @@
     "citation": 1,
     "license": 1,
     "verified_public_package": 10,
-    "publication_audit": 7
+    "publication_audit": 8
   },
   "artifacts": [
     {
@@ -465,7 +465,7 @@
       "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
       "exists": true,
       "bytes": 4432,
-      "sha256": "9848a62718df2058294e77349fb0f9f5af4f778a929ff50bad7c761419634015"
+      "sha256": "620e3238bd99516a89261c649b8d825ba335c851b4ff3f25f50a217ff9f2c446"
     },
     {
       "id": "source_alignment_validator",
@@ -486,8 +486,8 @@
       "surface": "repo_hf",
       "shows": "Publishes prepared Space, artifact dataset, and model bundles, including an explicit model-binary upload batch.",
       "exists": true,
-      "bytes": 22929,
-      "sha256": "3683a3d6ac1438999a110583a821fd2164ca50d191d2d5dca7921f2fb90f0977"
+      "bytes": 23694,
+      "sha256": "d8814ca59f4ea213c3a974682486d2c7c0284e41eb81b8cb2e0a09c8200f40f3"
     },
     {
       "id": "github_package_dockerfile",
@@ -585,8 +585,8 @@
       "surface": "website_hf",
       "shows": "Stores normalized 20-axis radar values, raw task metrics, Qwen3/Cosmos overlay mappings, branch-card caveats, and explicit scoreless status records.",
       "exists": true,
-      "bytes": 231282,
-      "sha256": "f07f229a075ea63156b3ad87588ea5f495fbb6db6d33bd6055fc4c9343447564"
+      "bytes": 231240,
+      "sha256": "394d494ab99e5d978415764ed785521c038881dd678f3036783be70fef068d25"
     },
     {
       "id": "single_episode_task_model_radar_json",
@@ -597,7 +597,7 @@
       "shows": "Machine-readable split radar for the one-episode Minimal and Neural MLP baselines, both scored on all 20 task contracts.",
       "exists": true,
       "bytes": 50973,
-      "sha256": "7bb8c7045ce277bd14a4ea4e433373af594a43825ce0fd818d0171400df7cb92"
+      "sha256": "fb1beb92720407bfe51933a064b2bb9f28d1e45fb17af0e673827d255ee92fab"
     },
     {
       "id": "episode128_task_model_radar_json",
@@ -607,8 +607,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable split radar for selected 128-episode metadata/raw baselines and verified Qwen3/Cosmos branches, preserving explicit scoreless cells.",
       "exists": true,
-      "bytes": 187431,
-      "sha256": "cf65729b44a6a678d14e9970ac809eb4fef688505dd5578c80c194650d6c1322"
+      "bytes": 187388,
+      "sha256": "a3b71765b2435f085a7bb0492e05dbfc4c3c9b06cb65a4ec326160abb31f6ad8"
     },
     {
       "id": "task_method_20_result_matrix_json",
@@ -618,8 +618,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable 9-method by 20-task matrix where every method has 20 records and scoreless cells carry unsupported/not-evaluated reasons.",
       "exists": true,
-      "bytes": 129771,
-      "sha256": "fa81542abb5fe7f0b8fd0cbeb29f8a8c8ce4f19a6e6ac3647c1078a554ee04be"
+      "bytes": 129749,
+      "sha256": "985d210609e40f06cb7d3d2819cd5e9330671a4506b1fb67c1917dcf4e2ea6e9"
     },
     {
       "id": "task_method_20_result_matrix",
@@ -629,8 +629,8 @@
       "surface": "repo_hf",
       "shows": "Reader-facing table that separates 20 records per method from numeric scored axes, documented raw128 proxy scores, unsupported metadata targets, and model targets not evaluated in verified packages.",
       "exists": true,
-      "bytes": 4208,
-      "sha256": "bfe01b258fe121448d2b5b188c6995041c81d7ce1286dcd2ee0bf9c01d6a6193"
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+      "sha256": "5a7f91a9d29e92ad66a698c0e3fb776b07f624a22f6eb972cbdb7354c3cfa4db"
     },
     {
       "id": "task_method_20_gap_audit_json",
@@ -640,8 +640,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable 180-record gap ledger with numeric scores, scoreless cells, explicit status reasons, and next evidence needed before new scores can be published.",
       "exists": true,
-      "bytes": 57943,
-      "sha256": "d9ce17695e9186e6ccb784d3c9af0d4e09addca71559526517bcc5f79f8bf89e"
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+      "sha256": "0049d8f850af3b47c100effde7d65940b63c3af2f91a5f29016bc3b066866576"
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     {
       "id": "task_method_20_gap_audit",
@@ -651,8 +651,8 @@
       "surface": "repo_hf",
       "shows": "Reader-facing ledger that lists every scoreless method-task cell and the concrete target or model-output evidence required before it can become numeric.",
       "exists": true,
-      "bytes": 16234,
-      "sha256": "01ae782b632d9f5c23cce5ebd7b99963cca9c4419193865bff434d9ec0b51dce"
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+      "sha256": "2585cbb6ffbb87cff3e16347f93947930c7059f1053d68b6f98a4c70ecc58654"
     },
     {
       "id": "unified_task_model_radar_chart",
@@ -662,8 +662,8 @@
       "surface": "website_hf",
       "shows": "Compares minimal and neural MLP baselines across all 20 tasks, with Qwen3/Cosmos task-aligned model overlays.",
       "exists": true,
-      "bytes": 49726,
-      "sha256": "1eb08975b1ee030bb2ca229eb68a68a6ffd8e7324d6870c7804997f676bc334a"
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+      "sha256": "eed2e19190d9760c35f6a66487762922fe42d3bd8de887cafbdad6ba4fd4122c"
     },
     {
       "id": "single_episode_task_model_radar_chart",
@@ -684,8 +684,8 @@
       "surface": "website_hf",
       "shows": "Separates the selected 128-episode methods: raw-feature simple/NN as complete 20/20 scored polygons and metadata/Qwen/Cosmos as task-aligned overlays.",
       "exists": true,
-      "bytes": 43710,
-      "sha256": "b8086051008c30ff5c224099023eab58883cb1ca025b2612231f4578ceec29a0"
+      "bytes": 44044,
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     },
     {
       "id": "unified_task_model_radar_builder",
@@ -894,7 +894,7 @@
       "shows": "Machine-readable visual asset index for website and Hugging Face mirrors.",
       "exists": true,
       "bytes": 17287,
-      "sha256": "66a495e656967f51f984f637c98aa4f3e5d16fdfdb05ae60660edebd84b0447d"
+      "sha256": "06a5854e14fb64e435d02e6fd5f476b37e9e3b981cf1d8b39fea3809f8ff5eaf"
     },
     {
       "id": "figure_index_builder",
@@ -971,7 +971,7 @@
       "shows": "Machine-readable release-check summary for validators, mirrors, and public project surfaces.",
       "exists": true,
       "bytes": 8100,
-      "sha256": "78dfe9c4e3b517a5db4e66a745d56503222b581d9fe9feaa96d2645410657667"
+      "sha256": "5dcf67ec345cace894593651ebfba6e99c120614e93f2b137287fca75b93305f"
     },
     {
       "id": "public_surface_qa",
@@ -1118,8 +1118,8 @@
       "surface": "repo_hf",
       "shows": "Generates the selective artifact catalog from local files.",
       "exists": true,
-      "bytes": 54683,
-      "sha256": "0a9e7c7391f0e2822d8490ddd216f155e1ce3a50d2ba3c90476ee09685f74d65"
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+      "sha256": "875106463eae01dc43f751fc5de15eb6f7ece55dc67bee7156b66fd85daebb5d"
     },
     {
       "id": "publication_audit",
@@ -1130,7 +1130,7 @@
       "volatile": true,
       "shows": "Confirms public bundles exclude raw data, caches, heavy archives, and credential text.",
       "exists": true,
-      "bytes": 8298,
+      "bytes": 13515,
       "hash_policy": "existence_and_size_only"
     },
     {
@@ -1154,7 +1154,7 @@
       "volatile": true,
       "shows": "Confirms prepared GitHub/HF Space/artifact/model mirrors share the same critical data, figure, website HTML, and validator files.",
       "exists": true,
-      "bytes": 871973,
+      "bytes": 899853,
       "hash_policy": "existence_and_size_only"
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@@ -2147,6 +2147,94 @@
       "exists": true,
       "bytes": 624,
       "sha256": "0723ecb9dd5cef371e2120af10903fc84a3ef495edafc8959f5eec0a778abbf1"
+    },
+    {
+      "id": "qwen3_future_task_probe_package",
+      "title": "Qwen3 v6 future-task probe package",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z",
+      "kind": "model_result",
+      "surface": "repo_hf",
+      "shows": "Two-shard Qwen3-Omni v6 inference probe for tasks 13, 14, and 17, with public-safe metrics, predictions, progress logs, and merge report.",
+      "exists": true,
+      "file_count": 17,
+      "bytes": 17786547
+    },
+    {
+      "id": "qwen3_future_task_probe_summary_json",
+      "title": "Qwen3 future-task probe merged summary",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/summary.json",
+      "kind": "metrics_source",
+      "surface": "repo_hf",
+      "shows": "Public-safe merged summary for xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.",
+      "exists": true,
+      "bytes": 1523,
+      "sha256": "80d33f6cb834d02192da560893aed13c4a1ec8fd3389290af35419a353779f0a"
+    },
+    {
+      "id": "qwen3_future_task_probe_collection_validation_json",
+      "title": "Qwen3 future-task probe collection validation",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/collection_validation.json",
+      "kind": "publication_audit",
+      "surface": "repo_hf",
+      "shows": "Public-safe collection validation for xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.",
+      "exists": true,
+      "bytes": 1307,
+      "sha256": "33ac6bff7d7111fb90b196801b93dfa199b637fb04983ace517aeda01f69e31b"
+    },
+    {
+      "id": "qwen3_future_task_probe_RUN_REPORT_md",
+      "title": "Qwen3 future-task probe run report",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/RUN_REPORT.md",
+      "kind": "scaleup_status",
+      "surface": "repo_hf",
+      "shows": "Public-safe run report for xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.",
+      "exists": true,
+      "bytes": 399,
+      "sha256": "927bee96928f9fe1380939a7ef4714405cfcf8c5af9f7bfe1ab403196983234a"
+    },
+    {
+      "id": "qwen3_future_task_probe_long_horizon_next_action_metrics_json",
+      "title": "Qwen3 future-task probe task 13 metrics",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/long_horizon_next_action/metrics.json",
+      "kind": "metrics_source",
+      "surface": "repo_hf",
+      "shows": "Public-safe task 13 metrics for xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.",
+      "exists": true,
+      "bytes": 13088,
+      "sha256": "5907654eba9013ada0e31302ce1cfe757c6f96510cdbdd2f97abadf383fedb3c"
+    },
+    {
+      "id": "qwen3_future_task_probe_next_subtask_forecast_metrics_json",
+      "title": "Qwen3 future-task probe task 14 metrics",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/metrics.json",
+      "kind": "metrics_source",
+      "surface": "repo_hf",
+      "shows": "Public-safe task 14 metrics for xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.",
+      "exists": true,
+      "bytes": 11425,
+      "sha256": "2fbb3f0d71fa963536dc90e4b4a3dc8ea4f935900a465018f0b44484234d5817"
+    },
+    {
+      "id": "qwen3_future_task_probe_object_set_forecast_metrics_json",
+      "title": "Qwen3 future-task probe task 17 metrics",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/metrics.json",
+      "kind": "metrics_source",
+      "surface": "repo_hf",
+      "shows": "Public-safe task 17 metrics for xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.",
+      "exists": true,
+      "bytes": 1481,
+      "sha256": "8d5dea02b20fb4b09aa33ab82309f76fa3a7e53bb86360ebc99b205a2e750302"
+    },
+    {
+      "id": "qwen3_future_task_probe_launcher_log",
+      "title": "Qwen3 future-task probe launcher log",
+      "path": "results/omni_finetune/deferred_launchers/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.launcher.log",
+      "kind": "scaleup_status",
+      "surface": "repo_hf",
+      "shows": "Launch and merge log for the two-shard future-task probe.",
+      "exists": true,
+      "bytes": 2048,
+      "sha256": "6952893720a78312f5a72b1f82cf59c1ec9b68520beb70cce96e2d0b8deb878b"
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   ]
 }
diff --git a/data/episode128_task_model_radar.json b/data/episode128_task_model_radar.json
index a982559ffcc9d87f2fa89b501b1ed328e1eee122..a3431c05080fee6a7fa617774854fc4b26ef36fc 100644
--- a/data/episode128_task_model_radar.json
+++ b/data/episode128_task_model_radar.json
@@ -1,12 +1,12 @@
 {
   "title": "128-Episode 20-Task Radar",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:06:55+00:00",
+  "generated_at_utc": "2026-06-17T07:04:16+00:00",
   "description": "Selected 128-episode metadata/raw baselines plus verified Qwen3/Cosmos branches. Every method has 20 records; numeric scores appear only where the public artifact produced that task target.",
   "task_count": 20,
   "method_count": 7,
   "method_task_record_count": 140,
-  "scored_method_task_count": 73,
+  "scored_method_task_count": 76,
   "normalization_policy": {
     "higher_is_better": "bounded metrics are plotted directly on 0-1 axes after clipping to [0, 1]",
     "lower_is_better": "lower-error metrics are converted to best_observed_value / raw_value within the same task",
@@ -127,17 +127,17 @@
       "method_detail": "Verified held-out Qwen3-Omni v6 LoRA metrics, plus task 16 and any completed private-GPU future-task probes scored from task-specific JSON.",
       "plotted_as": "colored point overlay",
       "result_record_count": 20,
-      "scored_task_count": 7,
-      "covered_task_count": 7,
+      "scored_task_count": 10,
+      "covered_task_count": 10,
       "proxy_scored_task_count": 0,
-      "scoreless_task_count": 13,
+      "scoreless_task_count": 10,
       "unsupported_task_count": 0,
-      "not_evaluated_task_count": 13,
+      "not_evaluated_task_count": 10,
       "status_counts": {
-        "not_evaluated_in_verified_package": 13,
-        "scored": 7
+        "not_evaluated_in_verified_package": 10,
+        "scored": 10
       },
-      "coverage_fraction": 0.35,
+      "coverage_fraction": 0.5,
       "result_record_fraction": 1.0
     },
     {
@@ -1339,15 +1339,15 @@
           "status_label": "scored"
         },
         "qwen3_omni_v6_lora": {
-          "raw": null,
-          "metric_key": "macro_f1",
-          "source": null,
+          "raw": 0.0023356666867101906,
+          "metric_key": "long_horizon_next_action_macro_f1",
+          "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/long_horizon_next_action/metrics.json",
           "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.0023356666867101906,
+          "raw_text": "0.0023",
+          "status_label": "scored"
         },
         "cosmos3_super_reasoner": {
           "raw": null,
@@ -1430,15 +1430,15 @@
           "status_label": "scored"
         },
         "qwen3_omni_v6_lora": {
-          "raw": null,
-          "metric_key": "macro_f1",
-          "source": null,
+          "raw": 0.004206715978529301,
+          "metric_key": "next_subtask_forecast_macro_f1",
+          "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/metrics.json",
           "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.004206715978529301,
+          "raw_text": "0.0042",
+          "status_label": "scored"
         },
         "cosmos3_super_reasoner": {
           "raw": null,
@@ -1703,15 +1703,15 @@
           "status_label": "scored"
         },
         "qwen3_omni_v6_lora": {
-          "raw": null,
-          "metric_key": "micro_f1",
-          "source": null,
+          "raw": 0.1659483964851402,
+          "metric_key": "object_set_forecast_micro_f1",
+          "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/metrics.json",
           "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.1659483964851402,
+          "raw_text": "0.1659",
+          "status_label": "scored"
         },
         "cosmos3_super_reasoner": {
           "raw": null,
@@ -3602,17 +3602,17 @@
       "task_label": "Long-Horizon Next-Action Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "macro_f1",
-      "source": null,
+      "raw": 0.0023356666867101906,
+      "raw_text": "0.0023",
+      "normalized_score": 0.0023356666867101906,
+      "metric_key": "long_horizon_next_action_macro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/long_horizon_next_action/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 13,
@@ -3728,17 +3728,17 @@
       "task_label": "Long-Horizon Next-Subtask Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "macro_f1",
-      "source": null,
+      "raw": 0.004206715978529301,
+      "raw_text": "0.0042",
+      "normalized_score": 0.004206715978529301,
+      "metric_key": "next_subtask_forecast_macro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 14,
@@ -4106,17 +4106,17 @@
       "task_label": "Future Object-Set Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "micro_f1",
-      "source": null,
+      "raw": 0.1659483964851402,
+      "raw_text": "0.1659",
+      "normalized_score": 0.1659483964851402,
+      "metric_key": "object_set_forecast_micro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 17,
diff --git a/data/figure_index.json b/data/figure_index.json
index 2f5f770d7cc45fecf36181e40dc40772020e0746..9fefee55e6f3fbce662b6ab23b0d64bf31fa45dd 100644
--- a/data/figure_index.json
+++ b/data/figure_index.json
@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Figure Index",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T11:33:21+00:00",
+  "generated_at_utc": "2026-06-17T07:06:27+00:00",
   "scope": "Public figures, diagrams, charts, and derived modality thumbnails. Raw Xperience-10M videos, annotations, RRD files, and Qwen weights are excluded.",
   "figure_count": 26,
   "figures": [
@@ -359,8 +359,8 @@
       "source_script": "scripts/build_unified_task_model_radar.py",
       "surface": "website unified task section, README, HF mirrors",
       "exists": true,
-      "bytes": 49046,
-      "sha256": "60c4ed6818b1ebf00165fc7187613c8e41bc0359d5053dfc3659f497f4acef44",
+      "bytes": 50060,
+      "sha256": "eed2e19190d9760c35f6a66487762922fe42d3bd8de887cafbdad6ba4fd4122c",
       "dimensions": {
         "format": "SVG",
         "width": 2400,
@@ -395,8 +395,8 @@
       "source_script": "scripts/build_unified_task_model_radar.py",
       "surface": "website unified task section, README, HF mirrors",
       "exists": true,
-      "bytes": 43020,
-      "sha256": "fad2d354e09ece917350dbbb66a65a4dcfabc38e000da61b002315c67b6aefa9",
+      "bytes": 44044,
+      "sha256": "fcaa7b7bcfb6662e479c968c1c1395e059bd272dd79694ce88637278e1d14d87",
       "dimensions": {
         "format": "SVG",
         "width": 2400,
diff --git a/data/mirror_parity.json b/data/mirror_parity.json
index 0f7188e3d2a27db8de79beb88588cb8311a91f64..8c25a1d11dab353c7f94b0f2b2e99d08c1e8c7fc 100644
--- a/data/mirror_parity.json
+++ b/data/mirror_parity.json
@@ -1,9 +1,9 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:07:43+00:00",
+  "generated_at_utc": "2026-06-17T07:23:26+00:00",
   "hf_root": "hf_publish",
   "summary": {
-    "group_count": 591,
+    "group_count": 609,
     "failure_count": 0,
     "failures_by_surface": {}
   },
@@ -138,45 +138,45 @@
       "local": {
         "path": "repo:docs/data/artifact_index.json",
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+          "sha256": "2585cbb6ffbb87cff3e16347f93947930c7059f1053d68b6f98a4c70ecc58654"
         },
         "hf_artifacts": {
           "path": "hf_artifacts:TASK_METHOD_20_GAP_AUDIT.md",
           "exists": true,
-          "bytes": 16234,
-          "sha256": "01ae782b632d9f5c23cce5ebd7b99963cca9c4419193865bff434d9ec0b51dce"
+          "bytes": 15690,
+          "sha256": "2585cbb6ffbb87cff3e16347f93947930c7059f1053d68b6f98a4c70ecc58654"
         },
         "hf_model": {
           "path": "hf_model:TASK_METHOD_20_GAP_AUDIT.md",
           "exists": true,
-          "bytes": 16234,
-          "sha256": "01ae782b632d9f5c23cce5ebd7b99963cca9c4419193865bff434d9ec0b51dce"
+          "bytes": 15690,
+          "sha256": "2585cbb6ffbb87cff3e16347f93947930c7059f1053d68b6f98a4c70ecc58654"
         }
       },
       "failures": []
@@ -18937,27 +19495,27 @@
       "local": {
         "path": "repo:TASK_METHOD_20_RESULT_MATRIX.md",
         "exists": true,
-        "bytes": 4208,
-        "sha256": "bfe01b258fe121448d2b5b188c6995041c81d7ce1286dcd2ee0bf9c01d6a6193"
+        "bytes": 4186,
+        "sha256": "5a7f91a9d29e92ad66a698c0e3fb776b07f624a22f6eb972cbdb7354c3cfa4db"
       },
       "mirrors": {
         "hf_space": {
           "path": "hf_space:TASK_METHOD_20_RESULT_MATRIX.md",
           "exists": true,
-          "bytes": 4208,
-          "sha256": "bfe01b258fe121448d2b5b188c6995041c81d7ce1286dcd2ee0bf9c01d6a6193"
+          "bytes": 4186,
+          "sha256": "5a7f91a9d29e92ad66a698c0e3fb776b07f624a22f6eb972cbdb7354c3cfa4db"
         },
         "hf_artifacts": {
           "path": "hf_artifacts:TASK_METHOD_20_RESULT_MATRIX.md",
           "exists": true,
-          "bytes": 4208,
-          "sha256": "bfe01b258fe121448d2b5b188c6995041c81d7ce1286dcd2ee0bf9c01d6a6193"
+          "bytes": 4186,
+          "sha256": "5a7f91a9d29e92ad66a698c0e3fb776b07f624a22f6eb972cbdb7354c3cfa4db"
         },
         "hf_model": {
           "path": "hf_model:TASK_METHOD_20_RESULT_MATRIX.md",
           "exists": true,
-          "bytes": 4208,
-          "sha256": "bfe01b258fe121448d2b5b188c6995041c81d7ce1286dcd2ee0bf9c01d6a6193"
+          "bytes": 4186,
+          "sha256": "5a7f91a9d29e92ad66a698c0e3fb776b07f624a22f6eb972cbdb7354c3cfa4db"
         }
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       "failures": []
diff --git a/data/public_surface_qa.json b/data/public_surface_qa.json
index fe7473073431f246d6446027373f0ff099b74593..39e9e1b85a00c02d61cd3189b6a1899bedfd5e5f 100644
--- a/data/public_surface_qa.json
+++ b/data/public_surface_qa.json
@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Public Project Surface",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T13:50:38+00:00",
+  "generated_at_utc": "2026-06-17T07:04:39+00:00",
   "scope": "Repo README, GitHub Pages HTML, Hugging Face Space card, artifact dataset card, and model card.",
   "checks": [
     {
@@ -18,7 +18,7 @@
         "website_integrity": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-16T13:35:52+00:00"
+          "generated_at_utc": "2026-06-16T15:07:46+00:00"
         },
         "rendered_site_check": {
           "exists": true,
@@ -28,12 +28,12 @@
         "task_surface_integrity": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-16T13:35:48+00:00"
+          "generated_at_utc": "2026-06-16T15:07:45+00:00"
         },
         "source_alignment": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-16T13:35:47+00:00"
+          "generated_at_utc": "2026-06-16T15:04:21+00:00"
         },
         "scale_up_status": {
           "exists": true,
@@ -43,12 +43,12 @@
         "publication_package": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-16T13:50:37+00:00"
+          "generated_at_utc": "2026-06-16T15:07:58+00:00"
         },
         "mirror_parity": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-16T13:50:22+00:00"
+          "generated_at_utc": "2026-06-16T15:07:43+00:00"
         }
       },
       "failures": {}
diff --git a/data/publication_audit.json b/data/publication_audit.json
index f95a362ee1f553da4d0af9eef53020cbf3338a83..09bc80358abcdb59932c30412f7e3153637b0f44 100644
--- a/data/publication_audit.json
+++ b/data/publication_audit.json
@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:07:58+00:00",
+  "generated_at_utc": "2026-06-17T07:22:48+00:00",
   "checks": [
     {
       "name": "required_publication_assets_present",
@@ -211,8 +211,8 @@
     "hf_space_bundle": {
       "root": "hf_publish/space",
       "exists": true,
-      "file_count": 984,
-      "text_file_count": 828,
+      "file_count": 1003,
+      "text_file_count": 841,
       "largest_file": {
         "path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
         "bytes": 55702978
@@ -222,8 +222,8 @@
     "hf_artifact_bundle": {
       "root": "hf_publish/artifacts",
       "exists": true,
-      "file_count": 2344,
-      "text_file_count": 1021,
+      "file_count": 2366,
+      "text_file_count": 1033,
       "largest_file": {
         "path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
         "bytes": 55702978
@@ -233,8 +233,8 @@
     "hf_model_bundle": {
       "root": "hf_publish/model",
       "exists": true,
-      "file_count": 2777,
-      "text_file_count": 1181,
+      "file_count": 2799,
+      "text_file_count": 1193,
       "largest_file": {
         "path": "pytorch_model.bin",
         "bytes": 93495480
diff --git a/data/quality_gates.json b/data/quality_gates.json
index 62fedc777d831f3caba1f8c848a27ee973354a54..37120a3d9d7eb14f60b3e27bf97c166834f2adb1 100644
--- a/data/quality_gates.json
+++ b/data/quality_gates.json
@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Release Checks",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:06:56+00:00",
+  "generated_at_utc": "2026-06-17T07:04:39+00:00",
   "rule": "A release is current when the automated reports pass and the live GitHub/Hugging Face mirrors are verified after publishing.",
   "automated_gates": [
     {
diff --git a/data/scope_claims_audit.json b/data/scope_claims_audit.json
index 4af6edc132281fc539642c1905e1efce8aa1ae80..ec03f30b93fd3a4f1bdca2abfeb0eebcc2d5bf74 100644
--- a/data/scope_claims_audit.json
+++ b/data/scope_claims_audit.json
@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-16T13:35:51+00:00",
+  "generated_at_utc": "2026-06-17T07:22:37+00:00",
   "summary": {
     "qwen3_omni_verified_diagnostic_pilot": true,
     "dataset_manifest_num_episodes": 119,
diff --git a/data/single_episode_task_model_radar.json b/data/single_episode_task_model_radar.json
index 1fa73eb7d9d0b66138e96b643c947a8879691ead..5b2ef9f01bd96175a17abd5d22731f8fe69de403 100644
--- a/data/single_episode_task_model_radar.json
+++ b/data/single_episode_task_model_radar.json
@@ -1,7 +1,7 @@
 {
   "title": "Single-Episode 20-Task Radar",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:06:55+00:00",
+  "generated_at_utc": "2026-06-17T07:04:16+00:00",
   "description": "Minimal and Neural MLP baselines on the one public sample episode, both scored on all 20 task contracts.",
   "task_count": 20,
   "method_count": 2,
diff --git a/data/source_alignment_audit.json b/data/source_alignment_audit.json
index 77027ebfb6fdab7ad9042b77cb8b75d8f7bff716..d6924d4b0628f1ca227b0b5300ac75880aea68b7 100644
--- a/data/source_alignment_audit.json
+++ b/data/source_alignment_audit.json
@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Source Alignment Note",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:04:21+00:00",
+  "generated_at_utc": "2026-06-17T07:22:34+00:00",
   "alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
   "alignment_summary": {
     "full_dataset_repo": "ropedia-ai/xperience-10m",
diff --git a/data/task_method_20_gap_audit.json b/data/task_method_20_gap_audit.json
index 1dca6b4ccf142c609a92caae664246bb51fd581b..e703c05c2e88a30979091d123c49d62ae9ff6805 100644
--- a/data/task_method_20_gap_audit.json
+++ b/data/task_method_20_gap_audit.json
@@ -1,10 +1,10 @@
 {
-  "generated_at_utc": "2026-06-16T15:06:55+00:00",
+  "generated_at_utc": "2026-06-17T07:04:39+00:00",
   "immediate_actions": [
     {
       "artifact": "docs/data/task_method_20_gap_audit.json",
       "id": "gap_audit",
-      "purpose": "Keep the 67 scoreless cells visible and reproducible."
+      "purpose": "Keep the 64 scoreless cells visible and reproducible."
     },
     {
       "artifact": "scripts/omni/score_model_output_probes.py",
@@ -101,11 +101,11 @@
       "proxy_scored_task_count": 0,
       "result_record_count": 20,
       "scope": "128 selected episodes, held-out test",
-      "scored_task_count": 7,
-      "scoreless_task_count": 13,
+      "scored_task_count": 10,
+      "scoreless_task_count": 10,
       "status_counts": {
-        "not_evaluated_in_verified_package": 13,
-        "scored": 7
+        "not_evaluated_in_verified_package": 10,
+        "scored": 10
       }
     },
     "raw128_neural_mlp": {
@@ -140,10 +140,10 @@
     "cosmos3_super_reasoner": 13,
     "metadata128_neural_mlp": 14,
     "metadata128_simple": 12,
-    "qwen3_omni_v6_lora": 13
+    "qwen3_omni_v6_lora": 10
   },
   "missing_by_status": {
-    "not_evaluated_in_verified_package": 41,
+    "not_evaluated_in_verified_package": 38,
     "not_supported_by_metadata_only_package": 22,
     "unsupported_without_required_target": 4
   },
@@ -197,15 +197,13 @@
       "cosmos3_nano_future_window",
       "cosmos3_super_reasoner",
       "metadata128_neural_mlp",
-      "metadata128_simple",
-      "qwen3_omni_v6_lora"
+      "metadata128_simple"
     ],
     "14 Long-Horizon Next-Subtask Forecasting": [
       "cosmos3_nano_future_window",
       "cosmos3_super_reasoner",
       "metadata128_neural_mlp",
-      "metadata128_simple",
-      "qwen3_omni_v6_lora"
+      "metadata128_simple"
     ],
     "15 Interaction Text Prediction": [
       "cosmos3_nano_future_window",
@@ -223,8 +221,7 @@
       "cosmos3_nano_future_window",
       "cosmos3_super_reasoner",
       "metadata128_neural_mlp",
-      "metadata128_simple",
-      "qwen3_omni_v6_lora"
+      "metadata128_simple"
     ],
     "18 IMU-to-Hand Pose Reconstruction": [
       "cosmos3_nano_future_window",
@@ -652,19 +649,6 @@
       "task_label": "Long-Horizon Next-Action Forecasting",
       "task_number": 13
     },
-    {
-      "method": "Qwen3-Omni v6 LoRA",
-      "metric_key": "macro_f1",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-      "recommended_next_step": "Generate verified model outputs for this task contract and score them against the held-out labels.",
-      "scope": "multi_episode_128_partial_model_overlay",
-      "series_id": "qwen3_omni_v6_lora",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "task_id": "long_horizon_next_action",
-      "task_label": "Long-Horizon Next-Action Forecasting",
-      "task_number": 13
-    },
     {
       "method": "Cosmos3-Super Reasoner",
       "metric_key": "macro_f1",
@@ -717,19 +701,6 @@
       "task_label": "Long-Horizon Next-Subtask Forecasting",
       "task_number": 14
     },
-    {
-      "method": "Qwen3-Omni v6 LoRA",
-      "metric_key": "macro_f1",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-      "recommended_next_step": "Generate verified model outputs for this task contract and score them against the held-out labels.",
-      "scope": "multi_episode_128_partial_model_overlay",
-      "series_id": "qwen3_omni_v6_lora",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "task_id": "next_subtask_forecast",
-      "task_label": "Long-Horizon Next-Subtask Forecasting",
-      "task_number": 14
-    },
     {
       "method": "Cosmos3-Super Reasoner",
       "metric_key": "macro_f1",
@@ -886,19 +857,6 @@
       "task_label": "Future Object-Set Forecasting",
       "task_number": 17
     },
-    {
-      "method": "Qwen3-Omni v6 LoRA",
-      "metric_key": "micro_f1",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-      "recommended_next_step": "Generate verified model outputs for this task contract and score them against the held-out labels.",
-      "scope": "multi_episode_128_partial_model_overlay",
-      "series_id": "qwen3_omni_v6_lora",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "task_id": "object_set_forecast",
-      "task_label": "Future Object-Set Forecasting",
-      "task_number": 17
-    },
     {
       "method": "Cosmos3-Super Reasoner",
       "metric_key": "micro_f1",
@@ -1167,8 +1125,8 @@
     "method_count": 9,
     "method_task_record_count": 180,
     "proxy_scored_method_task_count": 4,
-    "scored_method_task_count": 113,
-    "scoreless_method_task_count": 67,
+    "scored_method_task_count": 116,
+    "scoreless_method_task_count": 64,
     "task_count": 20
   },
   "source_matrix": "docs/data/task_method_20_result_matrix.json",
diff --git a/data/task_method_20_result_matrix.json b/data/task_method_20_result_matrix.json
index bdd0bd16f7ddc94fde61ba3728dade71b070a7a6..178dcb88c8b81452a418c9c35af500f94ab0811c 100644
--- a/data/task_method_20_result_matrix.json
+++ b/data/task_method_20_result_matrix.json
@@ -1,11 +1,11 @@
 {
   "title": "Task Method 20-Result Matrix",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:06:55+00:00",
+  "generated_at_utc": "2026-06-17T07:04:16+00:00",
   "task_count": 20,
   "method_count": 9,
   "method_task_record_count": 180,
-  "scored_method_task_count": 113,
+  "scored_method_task_count": 116,
   "series": [
     {
       "id": "minimal",
@@ -161,17 +161,17 @@
       "method_detail": "Verified held-out Qwen3-Omni v6 LoRA metrics, plus task 16 and any completed private-GPU future-task probes scored from task-specific JSON.",
       "plotted_as": "colored point overlay",
       "result_record_count": 20,
-      "scored_task_count": 7,
-      "covered_task_count": 7,
+      "scored_task_count": 10,
+      "covered_task_count": 10,
       "proxy_scored_task_count": 0,
-      "scoreless_task_count": 13,
+      "scoreless_task_count": 10,
       "unsupported_task_count": 0,
-      "not_evaluated_task_count": 13,
+      "not_evaluated_task_count": 10,
       "status_counts": {
-        "not_evaluated_in_verified_package": 13,
-        "scored": 7
+        "not_evaluated_in_verified_package": 10,
+        "scored": 10
       },
-      "coverage_fraction": 0.35,
+      "coverage_fraction": 0.5,
       "result_record_fraction": 1.0
     },
     {
@@ -2282,17 +2282,17 @@
       "task_label": "Long-Horizon Next-Action Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "macro_f1",
-      "source": null,
+      "raw": 0.0023356666867101906,
+      "raw_text": "0.0023",
+      "normalized_score": 0.0023356666867101906,
+      "metric_key": "long_horizon_next_action_macro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/long_horizon_next_action/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 13,
@@ -2444,17 +2444,17 @@
       "task_label": "Long-Horizon Next-Subtask Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "macro_f1",
-      "source": null,
+      "raw": 0.004206715978529301,
+      "raw_text": "0.0042",
+      "normalized_score": 0.004206715978529301,
+      "metric_key": "next_subtask_forecast_macro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 14,
@@ -2930,17 +2930,17 @@
       "task_label": "Future Object-Set Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "micro_f1",
-      "source": null,
+      "raw": 0.1659483964851402,
+      "raw_text": "0.1659",
+      "normalized_score": 0.1659483964851402,
+      "metric_key": "object_set_forecast_micro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 17,
diff --git a/data/task_surface_integrity.json b/data/task_surface_integrity.json
index 63b7feb1c61d4da3dc3fa3569a49366892285e40..c05f0ad7a86c11b628456a5c1484980cdd957ada 100644
--- a/data/task_surface_integrity.json
+++ b/data/task_surface_integrity.json
@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:07:45+00:00",
+  "generated_at_utc": "2026-06-17T07:22:34+00:00",
   "summary": {
     "task_count": 12,
     "expected_task_count": 12,
diff --git a/data/unified_task_model_radar.json b/data/unified_task_model_radar.json
index 111b8044f682f0385fca7e0886e8ffb8bd5ad89d..2c83f5937171a5c4945cbb5d446bb35554ec3112 100644
--- a/data/unified_task_model_radar.json
+++ b/data/unified_task_model_radar.json
@@ -1,11 +1,11 @@
 {
   "title": "Unified 20-Task Model Radar",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:06:55+00:00",
+  "generated_at_utc": "2026-06-17T07:04:16+00:00",
   "task_count": 20,
   "method_count": 9,
   "method_task_record_count": 180,
-  "scored_method_task_count": 113,
+  "scored_method_task_count": 116,
   "normalization_policy": {
     "higher_is_better": "bounded metrics are plotted directly on 0-1 axes after clipping to [0, 1]",
     "lower_is_better": "lower-error metrics are converted to best_observed_value / raw_value within the same task",
@@ -170,17 +170,17 @@
       "method_detail": "Verified held-out Qwen3-Omni v6 LoRA metrics, plus task 16 and any completed private-GPU future-task probes scored from task-specific JSON.",
       "plotted_as": "colored point overlay",
       "result_record_count": 20,
-      "scored_task_count": 7,
-      "covered_task_count": 7,
+      "scored_task_count": 10,
+      "covered_task_count": 10,
       "proxy_scored_task_count": 0,
-      "scoreless_task_count": 13,
+      "scoreless_task_count": 10,
       "unsupported_task_count": 0,
-      "not_evaluated_task_count": 13,
+      "not_evaluated_task_count": 10,
       "status_counts": {
-        "not_evaluated_in_verified_package": 13,
-        "scored": 7
+        "not_evaluated_in_verified_package": 10,
+        "scored": 10
       },
-      "coverage_fraction": 0.35,
+      "coverage_fraction": 0.5,
       "result_record_fraction": 1.0
     },
     {
@@ -1597,6 +1597,17 @@
           "raw_text": "0.0655",
           "status_label": "scored"
         },
+        "qwen3_omni_v6_lora": {
+          "raw": 0.0023356666867101906,
+          "metric_key": "long_horizon_next_action_macro_f1",
+          "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/long_horizon_next_action/metrics.json",
+          "scope": "multi_episode_128_partial_model_overlay",
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.0023356666867101906,
+          "raw_text": "0.0023",
+          "status_label": "scored"
+        },
         "raw128_simple": {
           "raw": 0.0024280172369056294,
           "metric_key": "macro_f1",
@@ -1641,17 +1652,6 @@
           "raw_text": "n/a",
           "status_label": "not supported"
         },
-        "qwen3_omni_v6_lora": {
-          "raw": null,
-          "metric_key": "macro_f1",
-          "source": null,
-          "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
-        },
         "cosmos3_super_reasoner": {
           "raw": null,
           "metric_key": "macro_f1",
@@ -1708,6 +1708,17 @@
           "raw_text": "0.0507",
           "status_label": "scored"
         },
+        "qwen3_omni_v6_lora": {
+          "raw": 0.004206715978529301,
+          "metric_key": "next_subtask_forecast_macro_f1",
+          "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/metrics.json",
+          "scope": "multi_episode_128_partial_model_overlay",
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.004206715978529301,
+          "raw_text": "0.0042",
+          "status_label": "scored"
+        },
         "raw128_simple": {
           "raw": 0.0,
           "metric_key": "macro_f1",
@@ -1752,17 +1763,6 @@
           "raw_text": "n/a",
           "status_label": "not supported"
         },
-        "qwen3_omni_v6_lora": {
-          "raw": null,
-          "metric_key": "macro_f1",
-          "source": null,
-          "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
-        },
         "cosmos3_super_reasoner": {
           "raw": null,
           "metric_key": "macro_f1",
@@ -2041,6 +2041,17 @@
           "raw_text": "0.1972",
           "status_label": "scored"
         },
+        "qwen3_omni_v6_lora": {
+          "raw": 0.1659483964851402,
+          "metric_key": "object_set_forecast_micro_f1",
+          "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/metrics.json",
+          "scope": "multi_episode_128_partial_model_overlay",
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.1659483964851402,
+          "raw_text": "0.1659",
+          "status_label": "scored"
+        },
         "raw128_simple": {
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           "metric_key": "micro_f1",
@@ -2085,17 +2096,6 @@
           "raw_text": "n/a",
           "status_label": "not supported"
         },
-        "qwen3_omni_v6_lora": {
-          "raw": null,
-          "metric_key": "micro_f1",
-          "source": null,
-          "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
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         "cosmos3_super_reasoner": {
           "raw": null,
           "metric_key": "micro_f1",
@@ -2492,7 +2492,7 @@
       "title": "Qwen3-Omni v6 LoRA",
       "status": "verified",
       "task_aligned_axes": "Qwen3",
-      "coverage": "20 records / 7 scored task-aligned axes",
+      "coverage": "20 records / 10 scored task-aligned axes",
       "headline": "JSON validity 0.9990; action macro-F1 0.0029",
       "source": "results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_multiscale_cap96_v6_rank64_lr5e5_full8gpu_lora_eval_test_full/eval/metrics.json"
     },
@@ -4580,17 +4580,17 @@
       "task_label": "Long-Horizon Next-Action Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "macro_f1",
-      "source": null,
+      "raw": 0.0023356666867101906,
+      "raw_text": "0.0023",
+      "normalized_score": 0.0023356666867101906,
+      "metric_key": "long_horizon_next_action_macro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/long_horizon_next_action/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 13,
@@ -4742,17 +4742,17 @@
       "task_label": "Long-Horizon Next-Subtask Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "macro_f1",
-      "source": null,
+      "raw": 0.004206715978529301,
+      "raw_text": "0.0042",
+      "normalized_score": 0.004206715978529301,
+      "metric_key": "next_subtask_forecast_macro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 14,
@@ -5228,17 +5228,17 @@
       "task_label": "Future Object-Set Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "micro_f1",
-      "source": null,
+      "raw": 0.1659483964851402,
+      "raw_text": "0.1659",
+      "normalized_score": 0.1659483964851402,
+      "metric_key": "object_set_forecast_micro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 17,
diff --git a/data/website_integrity.json b/data/website_integrity.json
index 22ebb4025323d37d53a5132e471f327bd0a2aa4b..dcc9d71445c39f19cc2470c69eb5fda7e828298c 100644
--- a/data/website_integrity.json
+++ b/data/website_integrity.json
@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:07:46+00:00",
+  "generated_at_utc": "2026-06-17T07:22:36+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
@@ -301,7 +301,7 @@
     },
     {
       "path": "data/artifact_index.json",
-      "bytes": 104199,
+      "bytes": 108681,
       "top_level_type": "dict"
     },
     {
@@ -316,7 +316,7 @@
     },
     {
       "path": "data/episode128_task_model_radar.json",
-      "bytes": 187431,
+      "bytes": 187388,
       "top_level_type": "dict"
     },
     {
@@ -346,7 +346,7 @@
     },
     {
       "path": "data/mirror_parity.json",
-      "bytes": 871973,
+      "bytes": 899853,
       "top_level_type": "dict"
     },
     {
@@ -391,7 +391,7 @@
     },
     {
       "path": "data/publication_audit.json",
-      "bytes": 8298,
+      "bytes": 8299,
       "top_level_type": "dict"
     },
     {
@@ -476,12 +476,12 @@
     },
     {
       "path": "data/task_method_20_gap_audit.json",
-      "bytes": 57943,
+      "bytes": 55745,
       "top_level_type": "dict"
     },
     {
       "path": "data/task_method_20_result_matrix.json",
-      "bytes": 129771,
+      "bytes": 129749,
       "top_level_type": "dict"
     },
     {
@@ -511,7 +511,7 @@
     },
     {
       "path": "data/unified_task_model_radar.json",
-      "bytes": 231282,
+      "bytes": 231240,
       "top_level_type": "dict"
     },
     {
@@ -551,7 +551,7 @@
     {
       "path": "assets/charts/episode128_task_model_radar.svg",
       "exists": true,
-      "bytes": 43710,
+      "bytes": 44044,
       "format": "SVG",
       "has_viewbox": true
     },
@@ -621,7 +621,7 @@
     {
       "path": "assets/charts/unified_task_model_radar.svg",
       "exists": true,
-      "bytes": 49726,
+      "bytes": 50060,
       "format": "SVG",
       "has_viewbox": true
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diff --git a/docs/assets/charts/episode128_task_model_radar.svg b/docs/assets/charts/episode128_task_model_radar.svg
index bd5d9c6b5203aba2d2bcc52bfcebbb0775a57f96..5aa6f68fc03b7e6e51ee53e3d5cde00127dcb13d 100644
--- a/docs/assets/charts/episode128_task_model_radar.svg
+++ b/docs/assets/charts/episode128_task_model_radar.svg
@@ -14,11 +14,11 @@
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 <text x="266.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#67e8d1" opacity="1.000">140 method-task records</text>
 <rect x="512" y="174" width="168" height="34" rx="17" fill="#22d3ee" fill-opacity="0.10" stroke="#22d3ee" stroke-opacity="0.38"/>
-<text x="528.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#22d3ee" opacity="1.000">73 scored axes</text>
+<text x="528.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#22d3ee" opacity="1.000">76 scored axes</text>
 <rect x="692" y="174" width="250" height="34" rx="17" fill="#f59e0b" fill-opacity="0.10" stroke="#f59e0b" stroke-opacity="0.38"/>
 <text x="708.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#f59e0b" opacity="1.000">40/40 raw128 pass</text>
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-<text x="970.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#f472b6" opacity="1.000">67 explicit scoreless</text>
+<text x="970.0" y="197.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="760" fill="#f472b6" opacity="1.000">64 explicit scoreless</text>
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 <text x="84.0" y="276.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="23" font-weight="800" fill="#f4f8ef" opacity="1.000">Normalized task scores</text>
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@@ -154,7 +154,10 @@
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@@ -191,7 +194,7 @@
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 <text x="1381.0" y="440.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="15" font-weight="800" fill="#f4f8ef" opacity="1.000">Qwen3-Omni v6 LoRA</text>
-<text x="1707.0" y="440.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="800" fill="#9bb8ff" opacity="1.000">20 records / 7 scored</text>
+<text x="1707.0" y="440.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="13" font-weight="800" fill="#9bb8ff" opacity="1.000">20 records / 10 scored</text>
 <text x="1381.0" y="460.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="11" font-weight="560" fill="#a5afa2" opacity="1.000">Verified held-out Qwen3-Omni v6 LoRA metrics, plus task 16 and any completed</text>
 <text x="1381.0" y="475.0" text-anchor="start" font-family="Space Grotesk, Arial, sans-serif" font-size="11" font-weight="560" fill="#a5afa2" opacity="1.000">private-GPU future-task probes scored from task-specific JSON.</text>
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diff --git a/docs/data/artifact_index.json b/docs/data/artifact_index.json
index 8b1986bd191650b42955308376e4e72e3bb00716..391bb70cc5215ef4b9babe10694cbb7183894969 100644
--- a/docs/data/artifact_index.json
+++ b/docs/data/artifact_index.json
@@ -1,13 +1,13 @@
 {
   "title": "Ropedia Xperience-10M Task Suite Artifact Index",
-  "generated_at_utc": "2026-06-16T15:06:56+00:00",
+  "generated_at_utc": "2026-06-17T07:20:47+00:00",
   "status": "pass",
-  "artifact_count": 191,
+  "artifact_count": 199,
   "missing": [],
   "by_kind": {
     "project_path": 14,
     "scaleup_contract": 7,
-    "scaleup_status": 42,
+    "scaleup_status": 44,
     "publication_workflow": 6,
     "reproducibility": 4,
     "project_scope": 1,
@@ -16,9 +16,9 @@
     "website_data": 10,
     "generated_figure": 7,
     "visualization_builder": 1,
-    "model_result": 3,
+    "model_result": 4,
     "result_interpretation": 5,
-    "metrics_source": 27,
+    "metrics_source": 31,
     "visual_evidence": 7,
     "dataset_context": 1,
     "quality_gate": 12,
@@ -35,7 +35,7 @@
     "citation": 1,
     "license": 1,
     "verified_public_package": 10,
-    "publication_audit": 7
+    "publication_audit": 8
   },
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     {
@@ -465,7 +465,7 @@
       "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
       "exists": true,
       "bytes": 4432,
-      "sha256": "9848a62718df2058294e77349fb0f9f5af4f778a929ff50bad7c761419634015"
+      "sha256": "620e3238bd99516a89261c649b8d825ba335c851b4ff3f25f50a217ff9f2c446"
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@@ -486,8 +486,8 @@
       "surface": "repo_hf",
       "shows": "Publishes prepared Space, artifact dataset, and model bundles, including an explicit model-binary upload batch.",
       "exists": true,
-      "bytes": 22929,
-      "sha256": "3683a3d6ac1438999a110583a821fd2164ca50d191d2d5dca7921f2fb90f0977"
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     },
     {
       "id": "github_package_dockerfile",
@@ -585,8 +585,8 @@
       "surface": "website_hf",
       "shows": "Stores normalized 20-axis radar values, raw task metrics, Qwen3/Cosmos overlay mappings, branch-card caveats, and explicit scoreless status records.",
       "exists": true,
-      "bytes": 231282,
-      "sha256": "f07f229a075ea63156b3ad87588ea5f495fbb6db6d33bd6055fc4c9343447564"
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     {
       "id": "single_episode_task_model_radar_json",
@@ -597,7 +597,7 @@
       "shows": "Machine-readable split radar for the one-episode Minimal and Neural MLP baselines, both scored on all 20 task contracts.",
       "exists": true,
       "bytes": 50973,
-      "sha256": "7bb8c7045ce277bd14a4ea4e433373af594a43825ce0fd818d0171400df7cb92"
+      "sha256": "fb1beb92720407bfe51933a064b2bb9f28d1e45fb17af0e673827d255ee92fab"
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     {
       "id": "episode128_task_model_radar_json",
@@ -607,8 +607,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable split radar for selected 128-episode metadata/raw baselines and verified Qwen3/Cosmos branches, preserving explicit scoreless cells.",
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@@ -618,8 +618,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable 9-method by 20-task matrix where every method has 20 records and scoreless cells carry unsupported/not-evaluated reasons.",
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-      "bytes": 129771,
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@@ -629,8 +629,8 @@
       "surface": "repo_hf",
       "shows": "Reader-facing table that separates 20 records per method from numeric scored axes, documented raw128 proxy scores, unsupported metadata targets, and model targets not evaluated in verified packages.",
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-      "bytes": 4208,
-      "sha256": "bfe01b258fe121448d2b5b188c6995041c81d7ce1286dcd2ee0bf9c01d6a6193"
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@@ -640,8 +640,8 @@
       "surface": "website_hf",
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-      "bytes": 57943,
-      "sha256": "d9ce17695e9186e6ccb784d3c9af0d4e09addca71559526517bcc5f79f8bf89e"
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@@ -651,8 +651,8 @@
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-      "sha256": "01ae782b632d9f5c23cce5ebd7b99963cca9c4419193865bff434d9ec0b51dce"
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       "id": "unified_task_model_radar_chart",
@@ -662,8 +662,8 @@
       "surface": "website_hf",
       "shows": "Compares minimal and neural MLP baselines across all 20 tasks, with Qwen3/Cosmos task-aligned model overlays.",
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-      "bytes": 49726,
-      "sha256": "1eb08975b1ee030bb2ca229eb68a68a6ffd8e7324d6870c7804997f676bc334a"
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     {
       "id": "single_episode_task_model_radar_chart",
@@ -684,8 +684,8 @@
       "surface": "website_hf",
       "shows": "Separates the selected 128-episode methods: raw-feature simple/NN as complete 20/20 scored polygons and metadata/Qwen/Cosmos as task-aligned overlays.",
       "exists": true,
-      "bytes": 43710,
-      "sha256": "b8086051008c30ff5c224099023eab58883cb1ca025b2612231f4578ceec29a0"
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@@ -894,7 +894,7 @@
       "shows": "Machine-readable visual asset index for website and Hugging Face mirrors.",
       "exists": true,
       "bytes": 17287,
-      "sha256": "66a495e656967f51f984f637c98aa4f3e5d16fdfdb05ae60660edebd84b0447d"
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@@ -971,7 +971,7 @@
       "shows": "Machine-readable release-check summary for validators, mirrors, and public project surfaces.",
       "exists": true,
       "bytes": 8100,
-      "sha256": "78dfe9c4e3b517a5db4e66a745d56503222b581d9fe9feaa96d2645410657667"
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@@ -1118,8 +1118,8 @@
       "surface": "repo_hf",
       "shows": "Generates the selective artifact catalog from local files.",
       "exists": true,
-      "bytes": 54683,
-      "sha256": "0a9e7c7391f0e2822d8490ddd216f155e1ce3a50d2ba3c90476ee09685f74d65"
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     {
       "id": "publication_audit",
@@ -1130,7 +1130,7 @@
       "volatile": true,
       "shows": "Confirms public bundles exclude raw data, caches, heavy archives, and credential text.",
       "exists": true,
-      "bytes": 8298,
+      "bytes": 13515,
       "hash_policy": "existence_and_size_only"
     },
     {
@@ -1154,7 +1154,7 @@
       "volatile": true,
       "shows": "Confirms prepared GitHub/HF Space/artifact/model mirrors share the same critical data, figure, website HTML, and validator files.",
       "exists": true,
-      "bytes": 871973,
+      "bytes": 899853,
       "hash_policy": "existence_and_size_only"
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@@ -2147,6 +2147,94 @@
       "exists": true,
       "bytes": 624,
       "sha256": "0723ecb9dd5cef371e2120af10903fc84a3ef495edafc8959f5eec0a778abbf1"
+    },
+    {
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+      "title": "Qwen3 v6 future-task probe package",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z",
+      "kind": "model_result",
+      "surface": "repo_hf",
+      "shows": "Two-shard Qwen3-Omni v6 inference probe for tasks 13, 14, and 17, with public-safe metrics, predictions, progress logs, and merge report.",
+      "exists": true,
+      "file_count": 17,
+      "bytes": 17786547
+    },
+    {
+      "id": "qwen3_future_task_probe_summary_json",
+      "title": "Qwen3 future-task probe merged summary",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/summary.json",
+      "kind": "metrics_source",
+      "surface": "repo_hf",
+      "shows": "Public-safe merged summary for xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.",
+      "exists": true,
+      "bytes": 1523,
+      "sha256": "80d33f6cb834d02192da560893aed13c4a1ec8fd3389290af35419a353779f0a"
+    },
+    {
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+      "title": "Qwen3 future-task probe collection validation",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/collection_validation.json",
+      "kind": "publication_audit",
+      "surface": "repo_hf",
+      "shows": "Public-safe collection validation for xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.",
+      "exists": true,
+      "bytes": 1307,
+      "sha256": "33ac6bff7d7111fb90b196801b93dfa199b637fb04983ace517aeda01f69e31b"
+    },
+    {
+      "id": "qwen3_future_task_probe_RUN_REPORT_md",
+      "title": "Qwen3 future-task probe run report",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/RUN_REPORT.md",
+      "kind": "scaleup_status",
+      "surface": "repo_hf",
+      "shows": "Public-safe run report for xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.",
+      "exists": true,
+      "bytes": 399,
+      "sha256": "927bee96928f9fe1380939a7ef4714405cfcf8c5af9f7bfe1ab403196983234a"
+    },
+    {
+      "id": "qwen3_future_task_probe_long_horizon_next_action_metrics_json",
+      "title": "Qwen3 future-task probe task 13 metrics",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/long_horizon_next_action/metrics.json",
+      "kind": "metrics_source",
+      "surface": "repo_hf",
+      "shows": "Public-safe task 13 metrics for xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.",
+      "exists": true,
+      "bytes": 13088,
+      "sha256": "5907654eba9013ada0e31302ce1cfe757c6f96510cdbdd2f97abadf383fedb3c"
+    },
+    {
+      "id": "qwen3_future_task_probe_next_subtask_forecast_metrics_json",
+      "title": "Qwen3 future-task probe task 14 metrics",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/metrics.json",
+      "kind": "metrics_source",
+      "surface": "repo_hf",
+      "shows": "Public-safe task 14 metrics for xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.",
+      "exists": true,
+      "bytes": 11425,
+      "sha256": "2fbb3f0d71fa963536dc90e4b4a3dc8ea4f935900a465018f0b44484234d5817"
+    },
+    {
+      "id": "qwen3_future_task_probe_object_set_forecast_metrics_json",
+      "title": "Qwen3 future-task probe task 17 metrics",
+      "path": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/metrics.json",
+      "kind": "metrics_source",
+      "surface": "repo_hf",
+      "shows": "Public-safe task 17 metrics for xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.",
+      "exists": true,
+      "bytes": 1481,
+      "sha256": "8d5dea02b20fb4b09aa33ab82309f76fa3a7e53bb86360ebc99b205a2e750302"
+    },
+    {
+      "id": "qwen3_future_task_probe_launcher_log",
+      "title": "Qwen3 future-task probe launcher log",
+      "path": "results/omni_finetune/deferred_launchers/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z.launcher.log",
+      "kind": "scaleup_status",
+      "surface": "repo_hf",
+      "shows": "Launch and merge log for the two-shard future-task probe.",
+      "exists": true,
+      "bytes": 2048,
+      "sha256": "6952893720a78312f5a72b1f82cf59c1ec9b68520beb70cce96e2d0b8deb878b"
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 }
diff --git a/docs/data/episode128_task_model_radar.json b/docs/data/episode128_task_model_radar.json
index a982559ffcc9d87f2fa89b501b1ed328e1eee122..a3431c05080fee6a7fa617774854fc4b26ef36fc 100644
--- a/docs/data/episode128_task_model_radar.json
+++ b/docs/data/episode128_task_model_radar.json
@@ -1,12 +1,12 @@
 {
   "title": "128-Episode 20-Task Radar",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:06:55+00:00",
+  "generated_at_utc": "2026-06-17T07:04:16+00:00",
   "description": "Selected 128-episode metadata/raw baselines plus verified Qwen3/Cosmos branches. Every method has 20 records; numeric scores appear only where the public artifact produced that task target.",
   "task_count": 20,
   "method_count": 7,
   "method_task_record_count": 140,
-  "scored_method_task_count": 73,
+  "scored_method_task_count": 76,
   "normalization_policy": {
     "higher_is_better": "bounded metrics are plotted directly on 0-1 axes after clipping to [0, 1]",
     "lower_is_better": "lower-error metrics are converted to best_observed_value / raw_value within the same task",
@@ -127,17 +127,17 @@
       "method_detail": "Verified held-out Qwen3-Omni v6 LoRA metrics, plus task 16 and any completed private-GPU future-task probes scored from task-specific JSON.",
       "plotted_as": "colored point overlay",
       "result_record_count": 20,
-      "scored_task_count": 7,
-      "covered_task_count": 7,
+      "scored_task_count": 10,
+      "covered_task_count": 10,
       "proxy_scored_task_count": 0,
-      "scoreless_task_count": 13,
+      "scoreless_task_count": 10,
       "unsupported_task_count": 0,
-      "not_evaluated_task_count": 13,
+      "not_evaluated_task_count": 10,
       "status_counts": {
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-        "scored": 7
+        "not_evaluated_in_verified_package": 10,
+        "scored": 10
       },
-      "coverage_fraction": 0.35,
+      "coverage_fraction": 0.5,
       "result_record_fraction": 1.0
     },
     {
@@ -1339,15 +1339,15 @@
           "status_label": "scored"
         },
         "qwen3_omni_v6_lora": {
-          "raw": null,
-          "metric_key": "macro_f1",
-          "source": null,
+          "raw": 0.0023356666867101906,
+          "metric_key": "long_horizon_next_action_macro_f1",
+          "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/long_horizon_next_action/metrics.json",
           "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.0023356666867101906,
+          "raw_text": "0.0023",
+          "status_label": "scored"
         },
         "cosmos3_super_reasoner": {
           "raw": null,
@@ -1430,15 +1430,15 @@
           "status_label": "scored"
         },
         "qwen3_omni_v6_lora": {
-          "raw": null,
-          "metric_key": "macro_f1",
-          "source": null,
+          "raw": 0.004206715978529301,
+          "metric_key": "next_subtask_forecast_macro_f1",
+          "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/metrics.json",
           "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.004206715978529301,
+          "raw_text": "0.0042",
+          "status_label": "scored"
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         "cosmos3_super_reasoner": {
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@@ -1703,15 +1703,15 @@
           "status_label": "scored"
         },
         "qwen3_omni_v6_lora": {
-          "raw": null,
-          "metric_key": "micro_f1",
-          "source": null,
+          "raw": 0.1659483964851402,
+          "metric_key": "object_set_forecast_micro_f1",
+          "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/metrics.json",
           "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
+          "status": "scored",
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+          "normalized_score": 0.1659483964851402,
+          "raw_text": "0.1659",
+          "status_label": "scored"
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         "cosmos3_super_reasoner": {
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@@ -3602,17 +3602,17 @@
       "task_label": "Long-Horizon Next-Action Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "macro_f1",
-      "source": null,
+      "raw": 0.0023356666867101906,
+      "raw_text": "0.0023",
+      "normalized_score": 0.0023356666867101906,
+      "metric_key": "long_horizon_next_action_macro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/long_horizon_next_action/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 13,
@@ -3728,17 +3728,17 @@
       "task_label": "Long-Horizon Next-Subtask Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "macro_f1",
-      "source": null,
+      "raw": 0.004206715978529301,
+      "raw_text": "0.0042",
+      "normalized_score": 0.004206715978529301,
+      "metric_key": "next_subtask_forecast_macro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 14,
@@ -4106,17 +4106,17 @@
       "task_label": "Future Object-Set Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "micro_f1",
-      "source": null,
+      "raw": 0.1659483964851402,
+      "raw_text": "0.1659",
+      "normalized_score": 0.1659483964851402,
+      "metric_key": "object_set_forecast_micro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
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     {
       "task_number": 17,
diff --git a/docs/data/figure_index.json b/docs/data/figure_index.json
index 2f5f770d7cc45fecf36181e40dc40772020e0746..9fefee55e6f3fbce662b6ab23b0d64bf31fa45dd 100644
--- a/docs/data/figure_index.json
+++ b/docs/data/figure_index.json
@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Figure Index",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T11:33:21+00:00",
+  "generated_at_utc": "2026-06-17T07:06:27+00:00",
   "scope": "Public figures, diagrams, charts, and derived modality thumbnails. Raw Xperience-10M videos, annotations, RRD files, and Qwen weights are excluded.",
   "figure_count": 26,
   "figures": [
@@ -359,8 +359,8 @@
       "source_script": "scripts/build_unified_task_model_radar.py",
       "surface": "website unified task section, README, HF mirrors",
       "exists": true,
-      "bytes": 49046,
-      "sha256": "60c4ed6818b1ebf00165fc7187613c8e41bc0359d5053dfc3659f497f4acef44",
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+      "sha256": "eed2e19190d9760c35f6a66487762922fe42d3bd8de887cafbdad6ba4fd4122c",
       "dimensions": {
         "format": "SVG",
         "width": 2400,
@@ -395,8 +395,8 @@
       "source_script": "scripts/build_unified_task_model_radar.py",
       "surface": "website unified task section, README, HF mirrors",
       "exists": true,
-      "bytes": 43020,
-      "sha256": "fad2d354e09ece917350dbbb66a65a4dcfabc38e000da61b002315c67b6aefa9",
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diff --git a/docs/data/mirror_parity.json b/docs/data/mirror_parity.json
index 0f7188e3d2a27db8de79beb88588cb8311a91f64..8c25a1d11dab353c7f94b0f2b2e99d08c1e8c7fc 100644
--- a/docs/data/mirror_parity.json
+++ b/docs/data/mirror_parity.json
@@ -1,9 +1,9 @@
 {
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+          "path": "hf_model:results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z_shard1.progress.jsonl",
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+          "sha256": "4fa85cd4d094eb4583f3f36f89f2662798268e33e2404fd440b39ff0199108ee"
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       "name": "results/single_episode_diagnostics/README.md",
       "status": "pass",
@@ -18906,27 +19464,27 @@
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-        "bytes": 16234,
-        "sha256": "01ae782b632d9f5c23cce5ebd7b99963cca9c4419193865bff434d9ec0b51dce"
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-          "bytes": 16234,
-          "sha256": "01ae782b632d9f5c23cce5ebd7b99963cca9c4419193865bff434d9ec0b51dce"
+          "bytes": 15690,
+          "sha256": "2585cbb6ffbb87cff3e16347f93947930c7059f1053d68b6f98a4c70ecc58654"
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         "hf_artifacts": {
           "path": "hf_artifacts:TASK_METHOD_20_GAP_AUDIT.md",
           "exists": true,
-          "bytes": 16234,
-          "sha256": "01ae782b632d9f5c23cce5ebd7b99963cca9c4419193865bff434d9ec0b51dce"
+          "bytes": 15690,
+          "sha256": "2585cbb6ffbb87cff3e16347f93947930c7059f1053d68b6f98a4c70ecc58654"
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         "hf_model": {
           "path": "hf_model:TASK_METHOD_20_GAP_AUDIT.md",
           "exists": true,
-          "bytes": 16234,
-          "sha256": "01ae782b632d9f5c23cce5ebd7b99963cca9c4419193865bff434d9ec0b51dce"
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@@ -18937,27 +19495,27 @@
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-        "bytes": 4208,
-        "sha256": "bfe01b258fe121448d2b5b188c6995041c81d7ce1286dcd2ee0bf9c01d6a6193"
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-          "bytes": 4208,
-          "sha256": "bfe01b258fe121448d2b5b188c6995041c81d7ce1286dcd2ee0bf9c01d6a6193"
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         "hf_artifacts": {
           "path": "hf_artifacts:TASK_METHOD_20_RESULT_MATRIX.md",
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-          "bytes": 4208,
-          "sha256": "bfe01b258fe121448d2b5b188c6995041c81d7ce1286dcd2ee0bf9c01d6a6193"
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         "hf_model": {
           "path": "hf_model:TASK_METHOD_20_RESULT_MATRIX.md",
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-          "bytes": 4208,
-          "sha256": "bfe01b258fe121448d2b5b188c6995041c81d7ce1286dcd2ee0bf9c01d6a6193"
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diff --git a/docs/data/public_surface_qa.json b/docs/data/public_surface_qa.json
index fe7473073431f246d6446027373f0ff099b74593..39e9e1b85a00c02d61cd3189b6a1899bedfd5e5f 100644
--- a/docs/data/public_surface_qa.json
+++ b/docs/data/public_surface_qa.json
@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Public Project Surface",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T13:50:38+00:00",
+  "generated_at_utc": "2026-06-17T07:04:39+00:00",
   "scope": "Repo README, GitHub Pages HTML, Hugging Face Space card, artifact dataset card, and model card.",
   "checks": [
     {
@@ -18,7 +18,7 @@
         "website_integrity": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-16T13:35:52+00:00"
+          "generated_at_utc": "2026-06-16T15:07:46+00:00"
         },
         "rendered_site_check": {
           "exists": true,
@@ -28,12 +28,12 @@
         "task_surface_integrity": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-16T13:35:48+00:00"
+          "generated_at_utc": "2026-06-16T15:07:45+00:00"
         },
         "source_alignment": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-16T13:35:47+00:00"
+          "generated_at_utc": "2026-06-16T15:04:21+00:00"
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@@ -43,12 +43,12 @@
         "publication_package": {
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           "status": "pass",
-          "generated_at_utc": "2026-06-16T13:50:37+00:00"
+          "generated_at_utc": "2026-06-16T15:07:58+00:00"
         },
         "mirror_parity": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-16T13:50:22+00:00"
+          "generated_at_utc": "2026-06-16T15:07:43+00:00"
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diff --git a/docs/data/publication_audit.json b/docs/data/publication_audit.json
index f95a362ee1f553da4d0af9eef53020cbf3338a83..09bc80358abcdb59932c30412f7e3153637b0f44 100644
--- a/docs/data/publication_audit.json
+++ b/docs/data/publication_audit.json
@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:07:58+00:00",
+  "generated_at_utc": "2026-06-17T07:22:48+00:00",
   "checks": [
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@@ -211,8 +211,8 @@
     "hf_space_bundle": {
       "root": "hf_publish/space",
       "exists": true,
-      "file_count": 984,
-      "text_file_count": 828,
+      "file_count": 1003,
+      "text_file_count": 841,
       "largest_file": {
         "path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
         "bytes": 55702978
@@ -222,8 +222,8 @@
     "hf_artifact_bundle": {
       "root": "hf_publish/artifacts",
       "exists": true,
-      "file_count": 2344,
-      "text_file_count": 1021,
+      "file_count": 2366,
+      "text_file_count": 1033,
       "largest_file": {
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         "bytes": 55702978
@@ -233,8 +233,8 @@
     "hf_model_bundle": {
       "root": "hf_publish/model",
       "exists": true,
-      "file_count": 2777,
-      "text_file_count": 1181,
+      "file_count": 2799,
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       "largest_file": {
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diff --git a/docs/data/quality_gates.json b/docs/data/quality_gates.json
index 62fedc777d831f3caba1f8c848a27ee973354a54..37120a3d9d7eb14f60b3e27bf97c166834f2adb1 100644
--- a/docs/data/quality_gates.json
+++ b/docs/data/quality_gates.json
@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Release Checks",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:06:56+00:00",
+  "generated_at_utc": "2026-06-17T07:04:39+00:00",
   "rule": "A release is current when the automated reports pass and the live GitHub/Hugging Face mirrors are verified after publishing.",
   "automated_gates": [
     {
diff --git a/docs/data/single_episode_task_model_radar.json b/docs/data/single_episode_task_model_radar.json
index 1fa73eb7d9d0b66138e96b643c947a8879691ead..5b2ef9f01bd96175a17abd5d22731f8fe69de403 100644
--- a/docs/data/single_episode_task_model_radar.json
+++ b/docs/data/single_episode_task_model_radar.json
@@ -1,7 +1,7 @@
 {
   "title": "Single-Episode 20-Task Radar",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:06:55+00:00",
+  "generated_at_utc": "2026-06-17T07:04:16+00:00",
   "description": "Minimal and Neural MLP baselines on the one public sample episode, both scored on all 20 task contracts.",
   "task_count": 20,
   "method_count": 2,
diff --git a/docs/data/source_alignment_audit.json b/docs/data/source_alignment_audit.json
index 77027ebfb6fdab7ad9042b77cb8b75d8f7bff716..d6924d4b0628f1ca227b0b5300ac75880aea68b7 100644
--- a/docs/data/source_alignment_audit.json
+++ b/docs/data/source_alignment_audit.json
@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Source Alignment Note",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:04:21+00:00",
+  "generated_at_utc": "2026-06-17T07:22:34+00:00",
   "alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
   "alignment_summary": {
     "full_dataset_repo": "ropedia-ai/xperience-10m",
diff --git a/docs/data/task_method_20_gap_audit.json b/docs/data/task_method_20_gap_audit.json
index 1dca6b4ccf142c609a92caae664246bb51fd581b..e703c05c2e88a30979091d123c49d62ae9ff6805 100644
--- a/docs/data/task_method_20_gap_audit.json
+++ b/docs/data/task_method_20_gap_audit.json
@@ -1,10 +1,10 @@
 {
-  "generated_at_utc": "2026-06-16T15:06:55+00:00",
+  "generated_at_utc": "2026-06-17T07:04:39+00:00",
   "immediate_actions": [
     {
       "artifact": "docs/data/task_method_20_gap_audit.json",
       "id": "gap_audit",
-      "purpose": "Keep the 67 scoreless cells visible and reproducible."
+      "purpose": "Keep the 64 scoreless cells visible and reproducible."
     },
     {
       "artifact": "scripts/omni/score_model_output_probes.py",
@@ -101,11 +101,11 @@
       "proxy_scored_task_count": 0,
       "result_record_count": 20,
       "scope": "128 selected episodes, held-out test",
-      "scored_task_count": 7,
-      "scoreless_task_count": 13,
+      "scored_task_count": 10,
+      "scoreless_task_count": 10,
       "status_counts": {
-        "not_evaluated_in_verified_package": 13,
-        "scored": 7
+        "not_evaluated_in_verified_package": 10,
+        "scored": 10
       }
     },
     "raw128_neural_mlp": {
@@ -140,10 +140,10 @@
     "cosmos3_super_reasoner": 13,
     "metadata128_neural_mlp": 14,
     "metadata128_simple": 12,
-    "qwen3_omni_v6_lora": 13
+    "qwen3_omni_v6_lora": 10
   },
   "missing_by_status": {
-    "not_evaluated_in_verified_package": 41,
+    "not_evaluated_in_verified_package": 38,
     "not_supported_by_metadata_only_package": 22,
     "unsupported_without_required_target": 4
   },
@@ -197,15 +197,13 @@
       "cosmos3_nano_future_window",
       "cosmos3_super_reasoner",
       "metadata128_neural_mlp",
-      "metadata128_simple",
-      "qwen3_omni_v6_lora"
+      "metadata128_simple"
     ],
     "14 Long-Horizon Next-Subtask Forecasting": [
       "cosmos3_nano_future_window",
       "cosmos3_super_reasoner",
       "metadata128_neural_mlp",
-      "metadata128_simple",
-      "qwen3_omni_v6_lora"
+      "metadata128_simple"
     ],
     "15 Interaction Text Prediction": [
       "cosmos3_nano_future_window",
@@ -223,8 +221,7 @@
       "cosmos3_nano_future_window",
       "cosmos3_super_reasoner",
       "metadata128_neural_mlp",
-      "metadata128_simple",
-      "qwen3_omni_v6_lora"
+      "metadata128_simple"
     ],
     "18 IMU-to-Hand Pose Reconstruction": [
       "cosmos3_nano_future_window",
@@ -652,19 +649,6 @@
       "task_label": "Long-Horizon Next-Action Forecasting",
       "task_number": 13
     },
-    {
-      "method": "Qwen3-Omni v6 LoRA",
-      "metric_key": "macro_f1",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-      "recommended_next_step": "Generate verified model outputs for this task contract and score them against the held-out labels.",
-      "scope": "multi_episode_128_partial_model_overlay",
-      "series_id": "qwen3_omni_v6_lora",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "task_id": "long_horizon_next_action",
-      "task_label": "Long-Horizon Next-Action Forecasting",
-      "task_number": 13
-    },
     {
       "method": "Cosmos3-Super Reasoner",
       "metric_key": "macro_f1",
@@ -717,19 +701,6 @@
       "task_label": "Long-Horizon Next-Subtask Forecasting",
       "task_number": 14
     },
-    {
-      "method": "Qwen3-Omni v6 LoRA",
-      "metric_key": "macro_f1",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-      "recommended_next_step": "Generate verified model outputs for this task contract and score them against the held-out labels.",
-      "scope": "multi_episode_128_partial_model_overlay",
-      "series_id": "qwen3_omni_v6_lora",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "task_id": "next_subtask_forecast",
-      "task_label": "Long-Horizon Next-Subtask Forecasting",
-      "task_number": 14
-    },
     {
       "method": "Cosmos3-Super Reasoner",
       "metric_key": "macro_f1",
@@ -886,19 +857,6 @@
       "task_label": "Future Object-Set Forecasting",
       "task_number": 17
     },
-    {
-      "method": "Qwen3-Omni v6 LoRA",
-      "metric_key": "micro_f1",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-      "recommended_next_step": "Generate verified model outputs for this task contract and score them against the held-out labels.",
-      "scope": "multi_episode_128_partial_model_overlay",
-      "series_id": "qwen3_omni_v6_lora",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "task_id": "object_set_forecast",
-      "task_label": "Future Object-Set Forecasting",
-      "task_number": 17
-    },
     {
       "method": "Cosmos3-Super Reasoner",
       "metric_key": "micro_f1",
@@ -1167,8 +1125,8 @@
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     "method_task_record_count": 180,
     "proxy_scored_method_task_count": 4,
-    "scored_method_task_count": 113,
-    "scoreless_method_task_count": 67,
+    "scored_method_task_count": 116,
+    "scoreless_method_task_count": 64,
     "task_count": 20
   },
   "source_matrix": "docs/data/task_method_20_result_matrix.json",
diff --git a/docs/data/task_method_20_result_matrix.json b/docs/data/task_method_20_result_matrix.json
index bdd0bd16f7ddc94fde61ba3728dade71b070a7a6..178dcb88c8b81452a418c9c35af500f94ab0811c 100644
--- a/docs/data/task_method_20_result_matrix.json
+++ b/docs/data/task_method_20_result_matrix.json
@@ -1,11 +1,11 @@
 {
   "title": "Task Method 20-Result Matrix",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:06:55+00:00",
+  "generated_at_utc": "2026-06-17T07:04:16+00:00",
   "task_count": 20,
   "method_count": 9,
   "method_task_record_count": 180,
-  "scored_method_task_count": 113,
+  "scored_method_task_count": 116,
   "series": [
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@@ -161,17 +161,17 @@
       "method_detail": "Verified held-out Qwen3-Omni v6 LoRA metrics, plus task 16 and any completed private-GPU future-task probes scored from task-specific JSON.",
       "plotted_as": "colored point overlay",
       "result_record_count": 20,
-      "scored_task_count": 7,
-      "covered_task_count": 7,
+      "scored_task_count": 10,
+      "covered_task_count": 10,
       "proxy_scored_task_count": 0,
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       "status_counts": {
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-        "scored": 7
+        "not_evaluated_in_verified_package": 10,
+        "scored": 10
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-      "coverage_fraction": 0.35,
+      "coverage_fraction": 0.5,
       "result_record_fraction": 1.0
     },
     {
@@ -2282,17 +2282,17 @@
       "task_label": "Long-Horizon Next-Action Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "macro_f1",
-      "source": null,
+      "raw": 0.0023356666867101906,
+      "raw_text": "0.0023",
+      "normalized_score": 0.0023356666867101906,
+      "metric_key": "long_horizon_next_action_macro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/long_horizon_next_action/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 13,
@@ -2444,17 +2444,17 @@
       "task_label": "Long-Horizon Next-Subtask Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "macro_f1",
-      "source": null,
+      "raw": 0.004206715978529301,
+      "raw_text": "0.0042",
+      "normalized_score": 0.004206715978529301,
+      "metric_key": "next_subtask_forecast_macro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 14,
@@ -2930,17 +2930,17 @@
       "task_label": "Future Object-Set Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "micro_f1",
-      "source": null,
+      "raw": 0.1659483964851402,
+      "raw_text": "0.1659",
+      "normalized_score": 0.1659483964851402,
+      "metric_key": "object_set_forecast_micro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
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     {
       "task_number": 17,
diff --git a/docs/data/task_surface_integrity.json b/docs/data/task_surface_integrity.json
index 63b7feb1c61d4da3dc3fa3569a49366892285e40..c05f0ad7a86c11b628456a5c1484980cdd957ada 100644
--- a/docs/data/task_surface_integrity.json
+++ b/docs/data/task_surface_integrity.json
@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:07:45+00:00",
+  "generated_at_utc": "2026-06-17T07:22:34+00:00",
   "summary": {
     "task_count": 12,
     "expected_task_count": 12,
diff --git a/docs/data/unified_task_model_radar.json b/docs/data/unified_task_model_radar.json
index 111b8044f682f0385fca7e0886e8ffb8bd5ad89d..2c83f5937171a5c4945cbb5d446bb35554ec3112 100644
--- a/docs/data/unified_task_model_radar.json
+++ b/docs/data/unified_task_model_radar.json
@@ -1,11 +1,11 @@
 {
   "title": "Unified 20-Task Model Radar",
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:06:55+00:00",
+  "generated_at_utc": "2026-06-17T07:04:16+00:00",
   "task_count": 20,
   "method_count": 9,
   "method_task_record_count": 180,
-  "scored_method_task_count": 113,
+  "scored_method_task_count": 116,
   "normalization_policy": {
     "higher_is_better": "bounded metrics are plotted directly on 0-1 axes after clipping to [0, 1]",
     "lower_is_better": "lower-error metrics are converted to best_observed_value / raw_value within the same task",
@@ -170,17 +170,17 @@
       "method_detail": "Verified held-out Qwen3-Omni v6 LoRA metrics, plus task 16 and any completed private-GPU future-task probes scored from task-specific JSON.",
       "plotted_as": "colored point overlay",
       "result_record_count": 20,
-      "scored_task_count": 7,
-      "covered_task_count": 7,
+      "scored_task_count": 10,
+      "covered_task_count": 10,
       "proxy_scored_task_count": 0,
-      "scoreless_task_count": 13,
+      "scoreless_task_count": 10,
       "unsupported_task_count": 0,
-      "not_evaluated_task_count": 13,
+      "not_evaluated_task_count": 10,
       "status_counts": {
-        "not_evaluated_in_verified_package": 13,
-        "scored": 7
+        "not_evaluated_in_verified_package": 10,
+        "scored": 10
       },
-      "coverage_fraction": 0.35,
+      "coverage_fraction": 0.5,
       "result_record_fraction": 1.0
     },
     {
@@ -1597,6 +1597,17 @@
           "raw_text": "0.0655",
           "status_label": "scored"
         },
+        "qwen3_omni_v6_lora": {
+          "raw": 0.0023356666867101906,
+          "metric_key": "long_horizon_next_action_macro_f1",
+          "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/long_horizon_next_action/metrics.json",
+          "scope": "multi_episode_128_partial_model_overlay",
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.0023356666867101906,
+          "raw_text": "0.0023",
+          "status_label": "scored"
+        },
         "raw128_simple": {
           "raw": 0.0024280172369056294,
           "metric_key": "macro_f1",
@@ -1641,17 +1652,6 @@
           "raw_text": "n/a",
           "status_label": "not supported"
         },
-        "qwen3_omni_v6_lora": {
-          "raw": null,
-          "metric_key": "macro_f1",
-          "source": null,
-          "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
-        },
         "cosmos3_super_reasoner": {
           "raw": null,
           "metric_key": "macro_f1",
@@ -1708,6 +1708,17 @@
           "raw_text": "0.0507",
           "status_label": "scored"
         },
+        "qwen3_omni_v6_lora": {
+          "raw": 0.004206715978529301,
+          "metric_key": "next_subtask_forecast_macro_f1",
+          "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/metrics.json",
+          "scope": "multi_episode_128_partial_model_overlay",
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.004206715978529301,
+          "raw_text": "0.0042",
+          "status_label": "scored"
+        },
         "raw128_simple": {
           "raw": 0.0,
           "metric_key": "macro_f1",
@@ -1752,17 +1763,6 @@
           "raw_text": "n/a",
           "status_label": "not supported"
         },
-        "qwen3_omni_v6_lora": {
-          "raw": null,
-          "metric_key": "macro_f1",
-          "source": null,
-          "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
-        },
         "cosmos3_super_reasoner": {
           "raw": null,
           "metric_key": "macro_f1",
@@ -2041,6 +2041,17 @@
           "raw_text": "0.1972",
           "status_label": "scored"
         },
+        "qwen3_omni_v6_lora": {
+          "raw": 0.1659483964851402,
+          "metric_key": "object_set_forecast_micro_f1",
+          "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/metrics.json",
+          "scope": "multi_episode_128_partial_model_overlay",
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.1659483964851402,
+          "raw_text": "0.1659",
+          "status_label": "scored"
+        },
         "raw128_simple": {
           "raw": 0.06469493412657774,
           "metric_key": "micro_f1",
@@ -2085,17 +2096,6 @@
           "raw_text": "n/a",
           "status_label": "not supported"
         },
-        "qwen3_omni_v6_lora": {
-          "raw": null,
-          "metric_key": "micro_f1",
-          "source": null,
-          "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
-        },
         "cosmos3_super_reasoner": {
           "raw": null,
           "metric_key": "micro_f1",
@@ -2492,7 +2492,7 @@
       "title": "Qwen3-Omni v6 LoRA",
       "status": "verified",
       "task_aligned_axes": "Qwen3",
-      "coverage": "20 records / 7 scored task-aligned axes",
+      "coverage": "20 records / 10 scored task-aligned axes",
       "headline": "JSON validity 0.9990; action macro-F1 0.0029",
       "source": "results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_multiscale_cap96_v6_rank64_lr5e5_full8gpu_lora_eval_test_full/eval/metrics.json"
     },
@@ -4580,17 +4580,17 @@
       "task_label": "Long-Horizon Next-Action Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "macro_f1",
-      "source": null,
+      "raw": 0.0023356666867101906,
+      "raw_text": "0.0023",
+      "normalized_score": 0.0023356666867101906,
+      "metric_key": "long_horizon_next_action_macro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/long_horizon_next_action/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 13,
@@ -4742,17 +4742,17 @@
       "task_label": "Long-Horizon Next-Subtask Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "macro_f1",
-      "source": null,
+      "raw": 0.004206715978529301,
+      "raw_text": "0.0042",
+      "normalized_score": 0.004206715978529301,
+      "metric_key": "next_subtask_forecast_macro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 14,
@@ -5228,17 +5228,17 @@
       "task_label": "Future Object-Set Forecasting",
       "series_id": "qwen3_omni_v6_lora",
       "method": "Qwen3-Omni v6 LoRA",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
-      "scored": false,
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "micro_f1",
-      "source": null,
+      "raw": 0.1659483964851402,
+      "raw_text": "0.1659",
+      "normalized_score": 0.1659483964851402,
+      "metric_key": "object_set_forecast_micro_f1",
+      "source": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
+      "reason": null
     },
     {
       "task_number": 17,
diff --git a/docs/data/website_integrity.json b/docs/data/website_integrity.json
index 22ebb4025323d37d53a5132e471f327bd0a2aa4b..dcc9d71445c39f19cc2470c69eb5fda7e828298c 100644
--- a/docs/data/website_integrity.json
+++ b/docs/data/website_integrity.json
@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-16T15:07:46+00:00",
+  "generated_at_utc": "2026-06-17T07:22:36+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
@@ -301,7 +301,7 @@
     },
     {
       "path": "data/artifact_index.json",
-      "bytes": 104199,
+      "bytes": 108681,
       "top_level_type": "dict"
     },
     {
@@ -316,7 +316,7 @@
     },
     {
       "path": "data/episode128_task_model_radar.json",
-      "bytes": 187431,
+      "bytes": 187388,
       "top_level_type": "dict"
     },
     {
@@ -346,7 +346,7 @@
     },
     {
       "path": "data/mirror_parity.json",
-      "bytes": 871973,
+      "bytes": 899853,
       "top_level_type": "dict"
     },
     {
@@ -391,7 +391,7 @@
     },
     {
       "path": "data/publication_audit.json",
-      "bytes": 8298,
+      "bytes": 8299,
       "top_level_type": "dict"
     },
     {
@@ -476,12 +476,12 @@
     },
     {
       "path": "data/task_method_20_gap_audit.json",
-      "bytes": 57943,
+      "bytes": 55745,
       "top_level_type": "dict"
     },
     {
       "path": "data/task_method_20_result_matrix.json",
-      "bytes": 129771,
+      "bytes": 129749,
       "top_level_type": "dict"
     },
     {
@@ -511,7 +511,7 @@
     },
     {
       "path": "data/unified_task_model_radar.json",
-      "bytes": 231282,
+      "bytes": 231240,
       "top_level_type": "dict"
     },
     {
@@ -551,7 +551,7 @@
     {
       "path": "assets/charts/episode128_task_model_radar.svg",
       "exists": true,
-      "bytes": 43710,
+      "bytes": 44044,
       "format": "SVG",
       "has_viewbox": true
     },
@@ -621,7 +621,7 @@
     {
       "path": "assets/charts/unified_task_model_radar.svg",
       "exists": true,
-      "bytes": 49726,
+      "bytes": 50060,
       "format": "SVG",
       "has_viewbox": true
     },
diff --git a/results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/predictions.jsonl b/results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/predictions.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..e4bc9663d118de82e5c74b57c00ac173f1155759
--- /dev/null
+++ b/results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/predictions.jsonl
@@ -0,0 +1,3951 @@
+{"correct": 0, "end_frame": 19, "episode_id": "1796b943-caad-43c6-b9bd-80b8d601f37d__ep1", "future_end_frame": 139, "future_start_frame": 100, "id": "dense_20f_stride10:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:0", "predicted_value": "Approaching workstation", "prediction_id": "next_subtask_forecast::dense_20f_stride10:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:0", "raw_prediction": "{\"next_subtask_forecast\":\"Approaching workstation\"}", "split": "test", "start_frame": 0, "target_future_id": "medium_40f_stride20:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:5", "task_id": "next_subtask_forecast", "task_label": "Long-Horizon Next-Subtask Forecasting", "true_value": "Entering the training area"}
+{"correct": 0, "end_frame": 79, "episode_id": "1796b943-caad-43c6-b9bd-80b8d601f37d__ep1", "future_end_frame": 139, "future_start_frame": 100, "id": "long_80f_stride40:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:0", "predicted_value": "Approaching workstation", "prediction_id": "next_subtask_forecast::long_80f_stride40:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:0", "raw_prediction": "{\"next_subtask_forecast\":\"Approaching workstation\"}", "split": "test", "start_frame": 0, "target_future_id": "medium_40f_stride20:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:5", "task_id": "next_subtask_forecast", "task_label": "Long-Horizon Next-Subtask Forecasting", "true_value": "Entering the training area"}
+{"correct": 0, "end_frame": 39, "episode_id": "1796b943-caad-43c6-b9bd-80b8d601f37d__ep1", "future_end_frame": 139, "future_start_frame": 100, "id": "medium_40f_stride20:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:0", "predicted_value": "Approaching workstation", "prediction_id": "next_subtask_forecast::medium_40f_stride20:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:0", "raw_prediction": "{\"next_subtask_forecast\":\"Approaching workstation\"}", "split": "test", "start_frame": 0, "target_future_id": "medium_40f_stride20:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:5", "task_id": "next_subtask_forecast", "task_label": "Long-Horizon Next-Subtask Forecasting", "true_value": "Entering the training area"}
+{"correct": 0, "end_frame": 29, "episode_id": "1796b943-caad-43c6-b9bd-80b8d601f37d__ep1", "future_end_frame": 159, "future_start_frame": 120, "id": "dense_20f_stride10:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:1", "predicted_value": "Approaching workstation", "prediction_id": "next_subtask_forecast::dense_20f_stride10:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:1", "raw_prediction": "{\"next_subtask_forecast\":\"Approaching workstation\"}", "split": "test", "start_frame": 10, "target_future_id": "medium_40f_stride20:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:6", "task_id": "next_subtask_forecast", "task_label": "Long-Horizon Next-Subtask Forecasting", "true_value": "Entering the training area"}
+{"correct": 0, "end_frame": 39, "episode_id": "1796b943-caad-43c6-b9bd-80b8d601f37d__ep1", "future_end_frame": 159, "future_start_frame": 120, "id": "dense_20f_stride10:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:2", "predicted_value": "Approaching workstation", "prediction_id": "next_subtask_forecast::dense_20f_stride10:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:2", "raw_prediction": "{\"next_subtask_forecast\":\"Approaching workstation\"}", "split": "test", "start_frame": 20, "target_future_id": "medium_40f_stride20:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:6", "task_id": "next_subtask_forecast", "task_label": "Long-Horizon Next-Subtask Forecasting", "true_value": "Entering the training area"}
+{"correct": 0, "end_frame": 59, "episode_id": "1796b943-caad-43c6-b9bd-80b8d601f37d__ep1", "future_end_frame": 159, "future_start_frame": 120, "id": "medium_40f_stride20:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:1", "predicted_value": "Approaching workstation", "prediction_id": "next_subtask_forecast::medium_40f_stride20:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:1", "raw_prediction": "{\"next_subtask_forecast\":\"Approaching workstation\"}", "split": "test", "start_frame": 20, "target_future_id": "medium_40f_stride20:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:6", "task_id": "next_subtask_forecast", "task_label": "Long-Horizon Next-Subtask Forecasting", "true_value": "Entering the training area"}
+{"correct": 0, "end_frame": 49, "episode_id": "1796b943-caad-43c6-b9bd-80b8d601f37d__ep1", "future_end_frame": 179, "future_start_frame": 140, "id": "dense_20f_stride10:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:3", "predicted_value": "Approaching workstation", "prediction_id": "next_subtask_forecast::dense_20f_stride10:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:3", "raw_prediction": "{\"next_subtask_forecast\":\"Approaching workstation\"}", "split": "test", "start_frame": 30, "target_future_id": "medium_40f_stride20:1796b943-caad-43c6-b9bd-80b8d601f37d__ep1:qa:7", "task_id": "next_subtask_forecast", "task_label": "Long-Horizon Next-Subtask Forecasting", "true_value": "Entering the training area"}
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diff --git a/results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/predictions.csv b/results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/predictions.csv
new file mode 100644
index 0000000000000000000000000000000000000000..792627854faaf8f7dfb3554c6ebe28f73dfcfc40
--- /dev/null
+++ b/results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/predictions.csv
@@ -0,0 +1,3992 @@
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+Note: The provided JSON is a prediction based on the visible context frames (4460-4499). The actual future window starting at frame 4560 may contain different objects.",0
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+Note: The provided JSON is based on the visible objects in the current frames (4470-4489) and the context of the activity. The prediction assumes the activity will continue as observed.",0
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+Note: The provided JSON is a prediction based on the visible context frames (4520-4599). The actual target at frame 4640 may differ.",0
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+
+Note: The prediction is based on the observed pattern of activity in the current frames, where individuals are consistently engaged with craft materials, pens, and paper on a table, with smartphones present for reference or recording. The future window is expected to continue this activity.",0
+long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:107,4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1,test,4720,4799,4840,"[""purple paper strip"", ""smartphone"", ""table""]","[""beads"", ""crafting tool"", ""paper craft"", ""pen"", ""person"", ""phone"", ""table""]","{""object_set_forecast"":[""person"",""table"",""phone"",""beads"",""pen"",""paper craft"",""crafting tool""]}",0
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+
+Note: The prediction is based on the observed activity of crafting with tassels and other materials, suggesting these items will remain in use.",0
+long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:109,4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1,test,4800,4879,4920,"[""purple paper strip"", ""smartphone"", ""table""]","[""beads"", ""crafting mat"", ""hands"", ""pen"", ""phone"", ""table""]","{""object_set_forecast"":[""beads"",""table"",""hands"",""phone"",""pen"",""crafting mat""]}",0
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+medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:155,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3400,3439,3500,"[""cardboard pieces"", ""marker"", ""ruler"", ""scissors""]","[""cardboard"", ""cardboard pieces"", ""glue gun"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""pencil"",""cardboard"",""ruler"",""glue gun"",""cardboard pieces""]}",0
+dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:326,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3410,3429,3520,"[""cardboard pieces"", ""marker"", ""ruler"", ""scissors""]","[""cardboard"", ""pen"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""cardboard"",""pencil"",""ruler"",""pen""]}",0
+dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:327,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3420,3439,3520,"[""cardboard pieces"", ""marker"", ""ruler"", ""scissors""]","[""cardboard pieces"", ""cardboard sheet"", ""glue gun"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""glue gun"",""cardboard pieces"",""pencil"",""ruler"",""cardboard sheet""]}",0
+medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:156,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3420,3459,3520,"[""cardboard pieces"", ""marker"", ""ruler"", ""scissors""]","[""cardboard"", ""pen"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""pencil"",""ruler"",""cardboard"",""pen""]}",0
+dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:328,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3430,3449,3540,"[""cardboard pieces"", ""marker"", ""ruler"", ""scissors""]","[""cardboard pieces"", ""cardboard sheet"", ""glue gun"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""glue gun"",""cardboard pieces"",""pencil"",""ruler"",""cardboard sheet""]}",0
+dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:329,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3440,3459,3540,"[""cardboard pieces"", ""marker"", ""ruler"", ""scissors""]","[""cardboard"", ""hand"", ""pen"", ""scissors"", ""table""]","{""object_set_forecast"":[""scissors"",""pen"",""cardboard"",""hand"",""table""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:71,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3440,3519,3540,"[""cardboard pieces"", ""marker"", ""ruler"", ""scissors""]","[""cardboard"", ""cardboard pieces"", ""glue gun"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""cardboard"",""scissors"",""pencil"",""ruler"",""glue gun"",""cardboard pieces""]}",0
+medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:157,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3440,3479,3540,"[""cardboard pieces"", ""marker"", ""ruler"", ""scissors""]","[""cardboard"", ""hand"", ""pen"", ""scissors"", ""table""]","{""object_set_forecast"":[""scissors"",""pen"",""cardboard"",""hand"",""table""]}",0
+dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:330,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3450,3469,3560,"[""cardboard pieces"", ""marker"", ""ruler""]","[""cardboard"", ""pen"", ""pile of cardboard"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""cardboard"",""ruler"",""pen"",""pile of cardboard""]}
+
+The person is using scissors to cut a piece of cardboard, with a ruler and pen nearby. They are working on a white surface with a large pile of cardboard pieces. The action of cutting and the presence of tools suggest that the person will continue to cut more cardboard pieces in the future.",0
+dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:331,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3460,3479,3560,"[""cardboard pieces"", ""marker"", ""ruler""]","[""cardboard scraps"", ""glue stick"", ""pencil"", ""ruler"", ""scissors"", ""wooden pieces""]","{""object_set_forecast"":[""scissors"",""glue stick"",""wooden pieces"",""pencil"",""ruler"",""cardboard scraps""]}",0
+medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:158,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3460,3499,3560,"[""cardboard pieces"", ""marker"", ""ruler""]","[""bowl"", ""box"", ""cardboard"", ""glue gun"", ""hand"", ""knife"", ""pen"", ""pencil"", ""ruler"", ""scissors"", ""table""]","{""object_set_forecast"":[""scissors"",""cardboard"",""hand"",""table"",""pencil"",""ruler"",""glue gun"",""box"",""pen"",""knife"",""bowl""]}",0
+dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:332,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3470,3489,3580,"[""cardboard pieces"", ""marker"", ""ruler""]","[""box cutter"", ""cardboard"", ""hand"", ""pencil"", ""ruler"", ""scissors"", ""table""]","{""object_set_forecast"":[""scissors"",""pencil"",""ruler"",""cardboard"",""box cutter"",""hand"",""table""]}",0
+dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:333,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3480,3499,3580,"[""cardboard pieces"", ""marker"", ""ruler""]","[""cardboard"", ""hand"", ""pencil"", ""ruler"", ""scissors"", ""table""]","{""object_set_forecast"":[""scissors"",""pencil"",""ruler"",""cardboard"",""hand"",""table""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:72,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3480,3559,3580,"[""cardboard pieces"", ""marker"", ""ruler""]","[""cardboard"", ""pen"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""pencil"",""cardboard"",""ruler"",""pen""]}",0
+medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:159,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3480,3519,3580,"[""cardboard pieces"", ""marker"", ""ruler""]","[""cardboard"", ""glue gun"", ""paper"", ""pen"", ""pile of paper"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""glue gun"",""scissors"",""ruler"",""paper"",""cardboard"",""pen"",""pile of paper""]}
+
+Note: The ""pile of paper"" is likely a typo in the original context and should be ""pile of cardboard"" as the person is working with cardboard pieces.",0
+medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:160,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3500,3539,3600,"[""cardboard pieces"", ""marker"", ""ruler""]","[""cardboard"", ""desk"", ""hand"", ""pen"", ""person"", ""scissors""]","{""object_set_forecast"":[""scissors"",""pen"",""cardboard"",""desk"",""hand"",""person""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:73,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3520,3599,3620,"[""cardboard pieces"", ""marker"", ""ruler""]","[""cardboard"", ""glue gun"", ""pencil"", ""ruler"", ""scissors"", ""stack of cardboard""]","{""object_set_forecast"":[""scissors"",""pencil"",""cardboard"",""ruler"",""glue gun"",""stack of cardboard""]}
+
+Note: The ""stack of cardboard"" is included as it is the most prominent object set in the scene and is likely to remain active.",0
+medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:161,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3520,3559,3620,"[""cardboard pieces"", ""marker"", ""ruler""]","[""cardboard"", ""cardboard pieces"", ""glue gun"", ""pen"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""pen"",""cardboard"",""ruler"",""glue gun"",""cardboard pieces""]}",0
+medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:162,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3540,3579,3640,"[""cardboard pieces"", ""marker"", ""ruler""]","[""cardboard"", ""cardboard pieces"", ""glue gun"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""pencil"",""cardboard"",""ruler"",""glue gun"",""cardboard pieces""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:74,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3560,3639,3680,"[""cardboard pieces"", ""marker"", ""ruler""]","[""box cutter"", ""cardboard"", ""pen"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""pen"",""cardboard"",""ruler"",""box cutter""]}",0
+medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:163,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3560,3599,3680,"[""cardboard pieces"", ""marker"", ""ruler""]","[""box cutter"", ""cardboard"", ""hand"", ""pen"", ""pile of cardboard"", ""ruler"", ""scissors"", ""table""]","{""object_set_forecast"":[""scissors"",""pen"",""cardboard"",""hand"",""table"",""box cutter"",""ruler"",""pile of cardboard""]}",0
+medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:164,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3580,3619,3680,"[""cardboard pieces"", ""marker"", ""ruler""]","[""cardboard"", ""cardboard pieces"", ""glue gun"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""cardboard"",""pencil"",""ruler"",""scissors"",""glue gun"",""cardboard pieces""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:75,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3600,3679,3720,"[""cardboard pieces"", ""marker"", ""ruler""]","[""cardboard"", ""cardboard pieces"", ""glue gun"", ""pen"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""pen"",""cardboard"",""ruler"",""glue gun"",""cardboard pieces""]}",0
+medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:165,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3600,3639,3720,"[""cardboard pieces"", ""marker"", ""ruler""]","[""cardboard"", ""cardboard pieces"", ""glue gun"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""pencil"",""cardboard"",""ruler"",""glue gun"",""cardboard pieces""]}",0
+medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:166,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3620,3659,3720,"[""cardboard pieces"", ""marker"", ""ruler""]","[""cardboard"", ""cardboard pieces"", ""marker"", ""pen"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""cardboard"",""marker"",""scissors"",""ruler"",""pen"",""cardboard pieces""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:76,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3640,3719,3800,"[""cardboard pieces"", ""marker"", ""metal ruler"", ""scissors""]","[""cardboard"", ""cardboard pieces"", ""glue gun"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""cardboard pieces"",""glue gun"",""scissors"",""cardboard"",""ruler""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:77,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3680,3759,3800,"[""cardboard pieces"", ""marker"", ""metal ruler"", ""scissors""]","[""cardboard pieces"", ""glue gun"", ""paper"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""glue gun"",""paper"",""pencil"",""ruler"",""cardboard pieces""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:78,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3720,3799,3840,"[""cardboard pieces"", ""marker"", ""metal ruler"", ""scissors""]","[""box cutter"", ""cardboard"", ""hand"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""pencil"",""ruler"",""cardboard"",""box cutter"",""hand""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:79,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3800,3879,3920,"[""cardboard pieces"", ""marker"", ""metal ruler"", ""scissors""]","[""cardboard"", ""cardboard pieces"", ""glue gun"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""glue gun"",""cardboard"",""ruler"",""pencil"",""cardboard pieces""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:80,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3840,3919,3960,"[""cardboard piece"", ""cardboard pieces"", ""marker"", ""metal ruler"", ""pencil case"", ""ruler"", ""scissors""]","[""box cutter"", ""cardboard"", ""pencil"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""cardboard"",""pencil"",""ruler"",""box cutter""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:81,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3880,3959,4000,"[""cardboard piece"", ""marker"", ""pencil case"", ""ruler"", ""scissors""]","[""craft paper"", ""craft pieces"", ""glue stick"", ""paper"", ""pencil"", ""scissors""]","{""object_set_forecast"":[""scissors"",""paper"",""pencil"",""glue stick"",""craft paper"",""craft pieces""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:82,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3920,3999,4040,"[""cardboard piece"", ""marker"", ""pencil case"", ""ruler"", ""scissors""]","[""box"", ""cardboard"", ""peanuts"", ""scissors"", ""tape""]","{""object_set_forecast"":[""scissors"",""tape"",""cardboard"",""peanuts"",""box""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:83,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,3960,4039,4080,"[""cardboard piece"", ""marker"", ""pencil case"", ""ruler"", ""scissors""]","[""box"", ""cardboard"", ""pen"", ""scissors"", ""tape""]","{""object_set_forecast"":[""scissors"",""cardboard"",""pen"",""tape"",""box""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:84,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,4000,4079,4600,"[""cardboard piece"", ""cardboard piles"", ""marker"", ""pouch"", ""ruler"", ""scissors""]","[""box"", ""cardboard"", ""nuts"", ""ruler"", ""scissors"", ""tape""]","{""object_set_forecast"":[""scissors"",""cardboard"",""nuts"",""box"",""tape"",""ruler""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:85,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,4040,4119,4600,"[""cardboard piece"", ""cardboard piles"", ""marker"", ""pouch"", ""ruler"", ""scissors""]","[""glue gun"", ""pencil"", ""red marker"", ""scissors"", ""wooden board"", ""wooden pieces""]","{""object_set_forecast"":[""scissors"",""glue gun"",""wooden pieces"",""wooden board"",""pencil"",""red marker""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:86,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,4080,4159,4600,"[""cardboard piece"", ""cardboard piles"", ""marker"", ""pouch"", ""ruler"", ""scissors""]","[""cardboard"", ""paper"", ""ruler"", ""scissors"", ""tape""]","{""object_set_forecast"":[""scissors"",""tape"",""cardboard"",""paper"",""ruler""]}",0
+dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:443,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,4600,4619,4700,"[""cardboard piece"", ""cardboard piles"", ""marker"", ""pouch"", ""ruler"", ""scissors""]","[""cardboard pieces"", ""cardboard sheet"", ""pen"", ""ruler"", ""scissors""]","{""object_set_forecast"":[""scissors"",""pen"",""cardboard pieces"",""ruler"",""cardboard sheet""]}",0
+long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:98,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,4600,4679,4700,"[""cardboard piece"", ""cardboard piles"", ""marker"", ""pouch"", ""ruler"", ""scissors""]","[""craft paper"", ""glue stick"", ""paper"", ""ruler"", ""scissors"", ""wooden pieces""]","{""object_set_forecast"":[""scissors"",""ruler"",""paper"",""glue stick"",""craft paper"",""wooden pieces""]}",0
+medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:213,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,4600,4639,4700,"[""cardboard piece"", ""cardboard piles"", ""marker"", ""pouch"", ""ruler"", ""scissors""]","[""paper"", ""pen"", ""puzzle box"", ""puzzle pieces"", ""scissors""]","{""object_set_forecast"":[""scissors"",""pen"",""paper"",""puzzle pieces"",""puzzle box""]}",0
+dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:444,9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2,test,4610,4629,4720,"[""cardboard piece"", ""cardboard piles"", ""marker"", ""pouch"", ""ruler"", ""scissors""]","[""cardboard"", ""hand"", ""paper"", ""scissors"", ""table""]","{""object_set_forecast"":[""scissors"",""paper"",""cardboard"",""hand"",""table""]}",0
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+dense_20f_stride10:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:392,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4020,4039,4120,"[""paper"", ""pen"", ""power bank"", ""smartphone"", ""star beads""]","[""black pouch"", ""cardboard stack"", ""colorful balls"", ""paper"", ""pen""]","{""object_set_forecast"":[""pen"",""paper"",""colorful balls"",""black pouch"",""cardboard stack""]}",0
+medium_40f_stride20:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:191,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4020,4059,4120,"[""paper"", ""pen"", ""power bank"", ""smartphone"", ""star beads""]","[""beads"", ""box"", ""desk"", ""hand"", ""paper"", ""pen"", ""person"", ""phone"", ""watch""]","{""object_set_forecast"":[""pen"",""paper"",""beads"",""box"",""hand"",""watch"",""phone"",""desk"",""person""]}",0
+dense_20f_stride10:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:393,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4030,4049,4160,"[""paper"", ""pen"", ""power bank"", ""smartphone"", ""star beads""]","[""bead bag"", ""bead tray"", ""colorful beads"", ""paper"", ""pen"", ""phone""]","{""object_set_forecast"":[""pen"",""paper"",""colorful beads"",""bead tray"",""phone"",""bead bag""]}",0
+dense_20f_stride10:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:394,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4040,4059,4160,"[""paper"", ""pen"", ""power bank"", ""smartphone"", ""star beads""]","[""beads"", ""box"", ""paper"", ""pen"", ""phone""]","{""object_set_forecast"":[""pen"",""paper"",""phone"",""beads"",""box""]}",0
+long_80f_stride40:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:91,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4040,4119,4160,"[""paper"", ""pen"", ""power bank"", ""smartphone"", ""star beads""]","[""beads"", ""box"", ""hand"", ""paper"", ""pen"", ""phone""]","{""object_set_forecast"":[""pen"",""paper"",""beads"",""box"",""phone"",""hand""]}
+
+Note: The prediction is based on the observed pattern of activity in the provided frames. The person is consistently interacting with the beads, pen, and paper, suggesting these items will remain active in the near future. The box and phone are also present and have been used, indicating potential future interaction. The hand is the active agent manipulating the objects.",0
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+medium_40f_stride20:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:193,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4060,4099,4160,"[""paper"", ""pen"", ""power bank"", ""smartphone"", ""star beads""]","[""box"", ""hand"", ""paper"", ""pen"", ""person"", ""phone"", ""rubber bands"", ""table""]","{""object_set_forecast"":[""pen"",""paper"",""rubber bands"",""hand"",""phone"",""box"",""table"",""person""]}",0
+long_80f_stride40:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:92,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4080,4159,4240,"[""paper"", ""pen"", ""star beads""]","[""box"", ""hand"", ""paper"", ""pen"", ""rubber bands"", ""stapler"", ""table""]","{""object_set_forecast"":[""pen"",""paper"",""rubber bands"",""stapler"",""box"",""hand"",""table""]}",0
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+long_80f_stride40:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:94,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4160,4239,4260,"[""paper"", ""pen"", ""star beads""]","[""box"", ""colorful rubber bands"", ""hand"", ""mask"", ""paper"", ""pen"", ""table"", ""watch""]","{""object_set_forecast"":[""pen"",""paper"",""colorful rubber bands"",""hand"",""table"",""box"",""mask"",""watch""]}",0
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+long_80f_stride40:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:95,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4240,4319,4340,"[""paper"", ""pen"", ""star beads""]","[""box"", ""hand"", ""paper"", ""pen"", ""phone"", ""rubber bands"", ""table""]","{""object_set_forecast"":[""pen"",""paper"",""rubber bands"",""phone"",""table"",""hand"",""box""]}",0
+medium_40f_stride20:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:201,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4240,4279,4340,"[""paper"", ""pen"", ""star beads""]","[""beads"", ""box"", ""hand"", ""paper"", ""pen"", ""phone"", ""table""]","{""object_set_forecast"":[""pen"",""paper"",""beads"",""phone"",""box"",""hand"",""table""]}",0
+dense_20f_stride10:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:414,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4250,4269,4400,"[""paper"", ""pen"", ""star beads""]","[""black pouch"", ""black wristband"", ""colorful rubber bands"", ""paper"", ""pen"", ""scissors""]","{""object_set_forecast"":[""pen"",""paper"",""colorful rubber bands"",""black wristband"",""scissors"",""black pouch""]}",0
+dense_20f_stride10:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:415,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4260,4279,4400,"[""paper"", ""pen"", ""star beads""]","[""black bag"", ""colorful beads"", ""paper"", ""pen"", ""smartphone""]","{""object_set_forecast"":[""pen"",""paper"",""colorful beads"",""smartphone"",""black bag""]}",0
+medium_40f_stride20:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:202,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4260,4299,4400,"[""paper"", ""pen"", ""star beads""]","[""box"", ""colorful balls"", ""hand"", ""paper"", ""pen"", ""phone"", ""table"", ""watch""]","{""object_set_forecast"":[""pen"",""paper"",""colorful balls"",""phone"",""watch"",""box"",""hand"",""table""]}",0
+dense_20f_stride10:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:416,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4270,4289,4400,"[""paper"", ""pen"", ""star beads""]","[""bead bracelet"", ""bead tray"", ""colorful beads"", ""paper"", ""pen"", ""phone"", ""rubik's cube""]","{""object_set_forecast"":[""pen"",""paper"",""phone"",""rubik's cube"",""colorful beads"",""bead bracelet"",""bead tray""]}",0
+dense_20f_stride10:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:417,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4280,4299,4400,"[""paper"", ""pen"", ""star beads""]","[""beads"", ""box"", ""paper"", ""pen"", ""phone"", ""watch""]","{""object_set_forecast"":[""pen"",""paper"",""beads"",""phone"",""watch"",""box""]}",0
+long_80f_stride40:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:96,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4280,4359,4400,"[""paper"", ""pen"", ""star beads""]","[""beads"", ""box"", ""paper"", ""pen"", ""phone"", ""watch""]","{""object_set_forecast"":[""pen"",""paper"",""beads"",""phone"",""watch"",""box""]}",0
+medium_40f_stride20:b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3:qa:203,b6579cb5-0a71-4ca6-8808-1e2700be05c7__ep3,test,4280,4319,4400,"[""paper"", ""pen"", ""star beads""]","[""beads"", ""box"", ""bracelet"", ""paper"", ""pen"", ""phone""]","{""object_set_forecast"":[""pen"",""paper"",""beads"",""phone"",""bracelet"",""box""]}",0
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+
+Note: The provided context frames (1490-1509) are before the requested future window (starting near frame 1590). The prediction is based on the observed activity of sorting and handling paper and pens.",0
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+long_80f_stride40:b750fab3-7fbb-43a0-b451-c64c4d4a64da__ep1:qa:120,b750fab3-7fbb-43a0-b451-c64c4d4a64da__ep1,test,5400,5479,5920,"[""beads"", ""smartphone"", ""yellow paper strip""]","[""paper"", ""pen"", ""pencil case"", ""phone"", ""sticky note""]","{""object_set_forecast"":[""sticky note"",""pen"",""phone"",""pencil case"",""paper""]}
+
+Note: The prediction is based on the current activity of folding sticky notes and the presence of related objects on the desk.",0
+dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:0,b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2,test,0,19,100,"[""paper pieces"", ""scissors"", ""smartphone""]","[""craft materials"", ""cup"", ""pen"", ""person"", ""phone"", ""scissors""]","{""object_set_forecast"":[""scissors"",""phone"",""craft materials"",""pen"",""cup"",""person""]}",0
+long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:0,b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2,test,0,79,100,"[""paper pieces"", ""scissors"", ""smartphone""]","[""craft paper"", ""pen"", ""phone"", ""puzzle pieces"", ""scissors""]","{""object_set_forecast"":[""scissors"",""phone"",""craft paper"",""puzzle pieces"",""pen""]}",0
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+dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:1,b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2,test,10,29,120,"[""paper pieces"", ""scissors"", ""smartphone""]","[""cup"", ""hand"", ""paper balls"", ""paper triangles"", ""pen"", ""phone"", ""scissors"", ""table""]","{""object_set_forecast"":[""scissors"",""phone"",""pen"",""paper balls"",""paper triangles"",""cup"",""hand"",""table""]}",0
+dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:2,b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2,test,20,39,120,"[""paper pieces"", ""scissors"", ""smartphone""]","[""craft paper"", ""glue stick"", ""pen"", ""pencil"", ""phone"", ""puzzle pieces"", ""scissors""]","{""object_set_forecast"":[""scissors"",""phone"",""craft paper"",""pencil"",""glue stick"",""puzzle pieces"",""pen""]}",0
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+dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:3,b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2,test,30,49,140,"[""paper pieces"", ""scissors"", ""smartphone""]","[""craft beads"", ""craft paper"", ""cup"", ""pen"", ""person"", ""phone"", ""scissors""]","{""object_set_forecast"":[""scissors"",""phone"",""craft beads"",""craft paper"",""pen"",""cup"",""person""]}",0
+dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:4,b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2,test,40,59,140,"[""paper pieces"", ""scissors"", ""smartphone""]","[""craft beads"", ""craft glue"", ""craft mat"", ""craft paper"", ""phone"", ""scissors""]","{""object_set_forecast"":[""scissors"",""phone"",""craft beads"",""craft paper"",""craft glue"",""craft mat""]}",0
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+dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:5,b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2,test,50,69,160,"[""paper pieces"", ""scissors"", ""smartphone""]","[""craft beads"", ""craft paper"", ""cup"", ""hand"", ""pen"", ""phone"", ""scissors"", ""table""]","{""object_set_forecast"":[""scissors"",""phone"",""craft beads"",""craft paper"",""pen"",""cup"",""hand"",""table""]}",0
+dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:6,b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2,test,60,79,160,"[""paper pieces"", ""scissors"", ""smartphone""]","[""paper"", ""pen"", ""phone"", ""pile of yellow paper"", ""scissors""]","{""object_set_forecast"":[""scissors"",""paper"",""phone"",""pen"",""pile of yellow paper""]}
+
+Note: The provided JSON is a prediction based on the visible objects in the current frames (60-79) and their likely continuation into the future window (starting near frame 160). The objects listed are those that are currently being interacted with or are part of the immediate activity.",0
+medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:3,b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2,test,60,99,160,"[""paper pieces"", ""scissors"", ""smartphone""]","[""colorful beads"", ""hand"", ""paper"", ""pen"", ""scissors"", ""smartphone"", ""table""]","{""object_set_forecast"":[""scissors"",""colorful beads"",""smartphone"",""paper"",""pen"",""hand"",""table""]}",0
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+dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:8,b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2,test,80,99,180,"[""paper pieces"", ""scissors"", ""smartphone""]","[""cup"", ""paper"", ""pen"", ""person"", ""phone"", ""pile of beads"", ""scissors""]","{""object_set_forecast"":[""scissors"",""phone"",""pile of beads"",""paper"",""pen"",""cup"",""person""]}",0
+long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:2,b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2,test,80,159,180,"[""paper pieces"", ""scissors"", ""smartphone""]","[""craft paper"", ""pen"", ""phone"", ""puzzle pieces"", ""scissors""]","{""object_set_forecast"":[""scissors"", ""phone"", ""craft paper"", ""puzzle pieces"", ""pen""]}",0
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+The future object set forecast is based on the observed activity of stringing colorful beads, with the scissors, mobile phone, and pen visible on the table. The stringing action suggests continued manipulation of the beads and string, while the paper may be used for organization or as a base. The scissors and mobile phone are likely to remain on the table for potential use or as reference.",0
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+Note: The prediction is based on the current activity of folding paper strips into fan shapes, with the scissors and smartphone remaining on the table. The pen is also present and could be used for marking or drawing. The paper fans are the current output of the activity.",0
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+dense_20f_stride10:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:188,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,1910,1929,2020,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""book"", ""bracelet"", ""desk"", ""earphone"", ""hand"", ""pen"", ""phone"", ""sticky notes"", ""water bottle""]","{""object_set_forecast"":[""phone"",""bracelet"",""water bottle"",""sticky notes"",""earphone"",""pen"",""book"",""hand"",""desk""]}",0
+dense_20f_stride10:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:189,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,1920,1939,2020,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""beads"", ""bracelet"", ""colorful paper"", ""earphone"", ""fan"", ""notebook"", ""pen"", ""scissors"", ""smartphone"", ""string"", ""water bottle""]","{""object_set_forecast"":[""beads"",""string"",""smartphone"",""water bottle"",""colorful paper"",""scissors"",""pen"",""notebook"",""bracelet"",""earphone"",""fan""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:45,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,1920,1999,2020,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""box"", ""bracelet"", ""card"", ""chair"", ""desk"", ""earphone"", ""fan"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""pen"",""phone"",""water bottle"",""paper"",""bracelet"",""earphone"",""card"",""box"",""desk"",""chair"",""fan""]}",0
+medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:93,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,1920,1959,2020,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""beads"", ""bracelet"", ""earphone"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""beads"",""pen"",""paper"",""water bottle"",""earphone"",""bracelet""]}",0
+dense_20f_stride10:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:190,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,1930,1949,2040,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""bracelet"", ""earbuds"", ""notebook"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""pen"",""notebook"",""water bottle"",""earbuds"",""bracelet""]}",0
+medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:94,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,1940,1979,2040,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""bracelet"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""pen"",""paper"",""water bottle"",""bracelet""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:46,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,1960,2039,2060,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""earphone"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""pen"",""paper"",""water bottle"",""earphone""]}",0
+medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:95,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,1960,1999,2060,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""bracelet"", ""chair"", ""earphone"", ""person"", ""phone"", ""table"", ""water bottle""]","{""object_set_forecast"":[""phone"",""bracelet"",""water bottle"",""earphone"",""table"",""chair"",""person""]}",0
+medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:96,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,1980,2019,2080,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""bracelet"", ""earphone"", ""paper"", ""pen"", ""phone"", ""tablet"", ""water bottle""]","{""object_set_forecast"":[""phone"",""bracelet"",""water bottle"",""tablet"",""paper"",""pen"",""earphone""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:47,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2000,2079,2120,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""box"", ""bracelet"", ""earphone"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""pen"",""paper"",""water bottle"",""bracelet"",""earphone"",""box""]}",0
+medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:97,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2000,2039,2120,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""bottle"", ""bracelet"", ""earphone"", ""paper"", ""pen"", ""phone""]","{""object_set_forecast"":[""phone"",""pen"",""paper"",""bottle"",""earphone"",""bracelet""]}",0
+medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:98,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2020,2059,2120,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""box"", ""earbud"", ""earbud case"", ""laptop"", ""pen"", ""phone"", ""sticky note"", ""table"", ""water bottle""]","{""object_set_forecast"":[""phone"",""earbud"",""box"",""table"",""water bottle"",""laptop"",""sticky note"",""pen"",""earbud case""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:48,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2040,2119,2160,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""cardboard"", ""earphone"", ""glue stick"", ""paper"", ""pen"", ""phone"", ""scissors"", ""water bottle""]","{""object_set_forecast"":[""phone"",""paper"",""pen"",""water bottle"",""earphone"",""cardboard"",""scissors"",""glue stick""]}",0
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+medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:100,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2060,2099,2160,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""bracelet"", ""papers"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""pen"",""water bottle"",""papers"",""bracelet""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:49,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2080,2159,2200,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""earphone"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""pen"",""paper"",""water bottle"",""earphone""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:50,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2120,2199,2240,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""bracelet"", ""laptop"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""pen"",""paper"",""water bottle"",""laptop"",""bracelet""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:51,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2160,2239,2280,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""bracelet"", ""earphone"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""pen"",""paper"",""water bottle"",""earphone"",""bracelet""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:52,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2200,2279,2320,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""water bottle""]","[""card"", ""earbuds"", ""laptop"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""card"",""pen"",""water bottle"",""laptop"",""earbuds""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:53,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2240,2319,2360,"[""jigsaw puzzle box"", ""paper strip"", ""phone"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""desk"", ""earphone"", ""laptop"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""pen"",""paper"",""water bottle"",""earphone"",""laptop"",""desk""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:54,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2280,2359,2400,"[""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""box cutter"", ""card"", ""chair"", ""desk"", ""earbuds"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""card"",""pen"",""water bottle"",""desk"",""chair"",""box cutter"",""earbuds""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:55,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2320,2399,2920,"[""decorative stars"", ""paper strips"", ""smartphone"", ""water bottle""]","[""colorful paper stack"", ""earbuds"", ""paper"", ""pen"", ""phone"", ""scissors"", ""water bottle""]","{""object_set_forecast"":[""phone"",""paper"",""scissors"",""pen"",""water bottle"",""earbuds"",""colorful paper stack""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:56,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2360,2439,2920,"[""decorative stars"", ""paper strips"", ""smartphone"", ""water bottle""]","[""beads"", ""bracelet"", ""person"", ""smartphone"", ""table"", ""water bottle""]","{""object_set_forecast"":[""beads"",""smartphone"",""water bottle"",""bracelet"",""table"",""person""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:57,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2400,2479,2920,"[""decorative stars"", ""paper strips"", ""smartphone"", ""water bottle""]","[""card"", ""chair"", ""desk"", ""earphone"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""card"",""pen"",""water bottle"",""earphone"",""paper"",""desk"",""chair""]}",0
+dense_20f_stride10:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:288,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2920,2939,3020,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""hand fan"", ""paper"", ""pen"", ""pencil case"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""pen"",""paper"",""water bottle"",""pencil case"",""hand fan""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:69,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2920,2999,3020,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""bracelet"", ""cardboard"", ""earphone"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""bracelet"",""pen"",""paper"",""water bottle"",""earphone"",""cardboard""]}
+
+Note: The prediction is based on the current activity of manipulating paper and the presence of tools like the pen and phone, suggesting continuation of the crafting task.",0
+medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:142,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2920,2959,3020,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""box"", ""desk"", ""earphone"", ""fan"", ""lamp"", ""papers"", ""pen"", ""person"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""person"",""desk"",""phone"",""fan"",""water bottle"",""papers"",""box"",""pen"",""earphone"",""lamp""]}",0
+dense_20f_stride10:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:289,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2930,2949,3030,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""earphone"", ""paper"", ""pen"", ""phone"", ""ruler"", ""water bottle""]","{""object_set_forecast"":[""phone"",""pen"",""paper"",""water bottle"",""ruler"",""earphone""]}",0
+dense_20f_stride10:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:290,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2940,2959,3040,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""bracelet"", ""earphone"", ""fan"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""pen"",""phone"",""water bottle"",""paper"",""bracelet"",""earphone"",""fan""]}",0
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+dense_20f_stride10:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:291,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2950,2969,3060,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""bracelet"", ""earphone"", ""paper"", ""pen"", ""ruler"", ""scissors"", ""smartphone"", ""water bottle""]","{""object_set_forecast"":[""smartphone"",""paper"",""scissors"",""ruler"",""pen"",""water bottle"",""earphone"",""bracelet""]}",0
+dense_20f_stride10:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:292,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2960,2979,3060,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""earphone"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""pen"",""paper"",""water bottle"",""earphone""]}",0
+long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:70,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2960,3039,3060,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""earphone"", ""paper"", ""pen"", ""smartphone"", ""water bottle""]","{""object_set_forecast"":[""smartphone"",""paper"",""pen"",""water bottle"",""earphone""]}",0
+medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:144,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2960,2999,3060,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""box"", ""bracelet"", ""earphone"", ""fan"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""bracelet"",""paper"",""pen"",""water bottle"",""earphone"",""box"",""fan""]}",0
+dense_20f_stride10:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:293,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2970,2989,3080,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""earphone"", ""paper"", ""pen"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""phone"",""pen"",""paper"",""water bottle"",""earphone""]}",0
+dense_20f_stride10:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:294,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2980,2999,3080,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""beads"", ""paper"", ""pen"", ""pencil case"", ""phone"", ""water bottle""]","{""object_set_forecast"":[""pen"",""phone"",""paper"",""beads"",""water bottle"",""pencil case""]}",0
+medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:145,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2980,3019,3080,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""earphone"", ""glue stick"", ""paper"", ""pencil"", ""phone"", ""poster"", ""ruler"", ""scissors"", ""water bottle""]","{""object_set_forecast"":[""phone"",""paper"",""scissors"",""glue stick"",""pencil"",""water bottle"",""poster"",""ruler"",""earphone""]}",0
+dense_20f_stride10:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:295,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,2990,3009,3100,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""earphone"", ""paper"", ""pen"", ""smartphone"", ""water bottle""]","{""object_set_forecast"":[""smartphone"",""paper"",""pen"",""water bottle"",""earphone""]}",0
+dense_20f_stride10:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:296,ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2,test,3000,3019,3100,"[""paper cone"", ""paper strip"", ""puzzle box"", ""smartphone"", ""water bottle""]","[""box cutter"", ""craft paper"", ""fan"", ""glue stick"", ""paper"", ""pen"", ""pencil"", ""phone"", ""ruler"", ""scissors"", ""water bottle""]","{""object_set_forecast"":[""phone"",""paper"",""scissors"",""glue stick"",""water bottle"",""pencil"",""ruler"",""craft paper"",""box cutter"",""fan"",""pen""]}",0
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diff --git a/results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/predictions.jsonl b/results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/predictions.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..1edd8a852800fa42eaeeee3f58d67727eba0bf80
--- /dev/null
+++ b/results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/predictions.jsonl
@@ -0,0 +1,3951 @@
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+{"correct": 0, "end_frame": 4539, "episode_id": "4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1", "future_end_frame": 4679, "future_start_frame": 4600, "id": "medium_40f_stride20:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:214", "predicted_value": ["pen", "pen cap", "person", "puzzle board", "puzzle pieces", "smartphone", "table"], "prediction_id": "object_set_forecast::medium_40f_stride20:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:214", "raw_prediction": "{\"object_set_forecast\":[\"person\",\"table\",\"puzzle pieces\",\"puzzle board\",\"pen\",\"smartphone\",\"pen cap\"]}", "split": "test", "start_frame": 4500, "target_future_id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:104", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["purple paper strip", "quilling paper pile", "smartphone"]}
+{"correct": 0, "end_frame": 4599, "episode_id": "4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1", "future_end_frame": 4719, "future_start_frame": 4640, "id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:102", "predicted_value": ["beads", "paper", "pen", "person", "phone", "table"], "prediction_id": "object_set_forecast::long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:102", "raw_prediction": "{\"object_set_forecast\":[\"person\",\"table\",\"phone\",\"beads\",\"pen\",\"paper\"]}\n\nNote: The provided JSON is a prediction based on the visible context frames (4520-4599). The actual target at frame 4640 may differ.", "split": "test", "start_frame": 4520, "target_future_id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:105", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["purple paper strip", "quilling paper pile", "smartphone"]}
+{"correct": 0, "end_frame": 4559, "episode_id": "4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1", "future_end_frame": 4719, "future_start_frame": 4640, "id": "medium_40f_stride20:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:215", "predicted_value": ["beads", "hands", "pen", "person", "phone", "table", "tassel"], "prediction_id": "object_set_forecast::medium_40f_stride20:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:215", "raw_prediction": "{\"object_set_forecast\":[\"hands\",\"pen\",\"phone\",\"table\",\"beads\",\"tassel\",\"person\"]}", "split": "test", "start_frame": 4520, "target_future_id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:105", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["purple paper strip", "quilling paper pile", "smartphone"]}
+{"correct": 0, "end_frame": 4579, "episode_id": "4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1", "future_end_frame": 4719, "future_start_frame": 4640, "id": "medium_40f_stride20:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:216", "predicted_value": ["craft material", "hands", "pen", "phone", "table"], "prediction_id": "object_set_forecast::medium_40f_stride20:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:216", "raw_prediction": "{\"object_set_forecast\":[\"hands\",\"phone\",\"craft material\",\"table\",\"pen\"]}", "split": "test", "start_frame": 4540, "target_future_id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:105", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["purple paper strip", "quilling paper pile", "smartphone"]}
+{"correct": 0, "end_frame": 4639, "episode_id": "4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1", "future_end_frame": 4759, "future_start_frame": 4680, "id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:103", "predicted_value": ["beads", "box", "pen", "person", "phone", "table", "tassel"], "prediction_id": "object_set_forecast::long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:103", "raw_prediction": "{\"object_set_forecast\":[\"person\",\"table\",\"pen\",\"phone\",\"beads\",\"tassel\",\"box\"]}", "split": "test", "start_frame": 4560, "target_future_id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:106", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["purple paper strip", "quilling paper pile", "smartphone"]}
+{"correct": 0, "end_frame": 4599, "episode_id": "4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1", "future_end_frame": 4759, "future_start_frame": 4680, "id": "medium_40f_stride20:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:217", "predicted_value": ["beads", "crafting tool", "hands", "paper", "pen", "phone", "table"], "prediction_id": "object_set_forecast::medium_40f_stride20:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:217", "raw_prediction": "{\"object_set_forecast\":[\"hands\",\"phone\",\"beads\",\"table\",\"pen\",\"paper\",\"crafting tool\"]}", "split": "test", "start_frame": 4560, "target_future_id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:106", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["purple paper strip", "quilling paper pile", "smartphone"]}
+{"correct": 0, "end_frame": 4679, "episode_id": "4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1", "future_end_frame": 4799, "future_start_frame": 4720, "id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:104", "predicted_value": ["hands", "pen", "puzzle board", "puzzle box", "puzzle pieces", "smartphone"], "prediction_id": "object_set_forecast::long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:104", "raw_prediction": "{\"object_set_forecast\":[\"puzzle pieces\",\"puzzle board\",\"hands\",\"puzzle box\",\"smartphone\",\"pen\"]}", "split": "test", "start_frame": 4600, "target_future_id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:107", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["purple paper strip", "quilling paper pile", "smartphone"]}
+{"correct": 0, "end_frame": 4719, "episode_id": "4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1", "future_end_frame": 4839, "future_start_frame": 4760, "id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:105", "predicted_value": ["beads", "crafting mat", "pen", "person", "phone", "table"], "prediction_id": "object_set_forecast::long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:105", "raw_prediction": "{\"object_set_forecast\":[\"person\",\"table\",\"phone\",\"beads\",\"pen\",\"crafting mat\"]}", "split": "test", "start_frame": 4640, "target_future_id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:108", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["purple paper strip", "quilling paper pile", "smartphone", "table"]}
+{"correct": 0, "end_frame": 4759, "episode_id": "4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1", "future_end_frame": 4879, "future_start_frame": 4800, "id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:106", "predicted_value": ["craft material", "paper", "pen", "person", "smartphone", "table"], "prediction_id": "object_set_forecast::long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:106", "raw_prediction": "{\"object_set_forecast\":[\"person\",\"table\",\"smartphone\",\"craft material\",\"pen\",\"paper\"]}\n\nNote: The prediction is based on the observed pattern of activity in the current frames, where individuals are consistently engaged with craft materials, pens, and paper on a table, with smartphones present for reference or recording. The future window is expected to continue this activity.", "split": "test", "start_frame": 4680, "target_future_id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:109", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["purple paper strip", "smartphone", "table"]}
+{"correct": 0, "end_frame": 4799, "episode_id": "4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1", "future_end_frame": 4919, "future_start_frame": 4840, "id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:107", "predicted_value": ["beads", "crafting tool", "paper craft", "pen", "person", "phone", "table"], "prediction_id": "object_set_forecast::long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:107", "raw_prediction": "{\"object_set_forecast\":[\"person\",\"table\",\"phone\",\"beads\",\"pen\",\"paper craft\",\"crafting tool\"]}", "split": "test", "start_frame": 4720, "target_future_id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:110", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["purple paper strip", "smartphone", "table"]}
+{"correct": 0, "end_frame": 4839, "episode_id": "4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1", "future_end_frame": 4959, "future_start_frame": 4880, "id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:108", "predicted_value": ["craft material", "glue", "paper", "pen", "person", "phone", "scissors", "table", "tassel"], "prediction_id": "object_set_forecast::long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:108", "raw_prediction": "{\"object_set_forecast\":[\"person\",\"table\",\"phone\",\"craft material\",\"pen\",\"tassel\",\"scissors\",\"glue\",\"paper\"]}\n\nNote: The prediction is based on the observed activity of crafting with tassels and other materials, suggesting these items will remain in use.", "split": "test", "start_frame": 4760, "target_future_id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:111", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["purple paper strip", "smartphone", "table"]}
+{"correct": 0, "end_frame": 4879, "episode_id": "4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1", "future_end_frame": 4999, "future_start_frame": 4920, "id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:109", "predicted_value": ["beads", "crafting mat", "hands", "pen", "phone", "table"], "prediction_id": "object_set_forecast::long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:109", "raw_prediction": "{\"object_set_forecast\":[\"beads\",\"table\",\"hands\",\"phone\",\"pen\",\"crafting mat\"]}", "split": "test", "start_frame": 4800, "target_future_id": "long_80f_stride40:4b02bb38-384a-438a-b5f9-6131d85c34b0__ep1:qa:112", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["purple paper strip", "smartphone", "table"]}
+{"correct": 0, "end_frame": 19, "episode_id": "5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6", "future_end_frame": 139, "future_start_frame": 100, "id": "dense_20f_stride10:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:0", "predicted_value": ["bathroom", "bathtub", "bed", "bedroom", "box", "cabinet", "chair", "closet", "couch", "desk", "door", "elevator", "escalator", "floor", "hallway", "kitchen", "light", "living room", "microwave", "mirror", "oven", "person", "phone", "refrigerator", "rug", "shelf", "shower", "sink", "staircase", "stove", "table", "toilet", "trash can", "wall", "wardrobe", "window"], "prediction_id": "object_set_forecast::dense_20f_stride10:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:0", "raw_prediction": "{\"object_set_forecast\":[\"person\",\"phone\",\"door\",\"light\",\"wall\",\"floor\",\"rug\",\"box\",\"shelf\",\"table\",\"cabinet\",\"refrigerator\",\"microwave\",\"oven\",\"sink\",\"toilet\",\"bathtub\",\"shower\",\"mirror\",\"stove\",\"trash can\",\"chair\",\"desk\",\"window\",\"couch\",\"bed\",\"closet\",\"wardrobe\",\"staircase\",\"elevator\",\"escalator\",\"bathroom\",\"kitchen\",\"living room\",\"bedroom\",\"hallway\",\"closet\",\"wardrobe\",\"staircase\",\"elevator\",\"escalator\",\"bathroom\",\"kitchen\",\"living room\",\"bedroom\",\"hallway\"]}", "split": "test", "start_frame": 0, "target_future_id": "medium_40f_stride20:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:5", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["jigsaw puzzle", "puzzle piece"]}
+{"correct": 0, "end_frame": 79, "episode_id": "5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6", "future_end_frame": 139, "future_start_frame": 100, "id": "long_80f_stride40:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:0", "predicted_value": ["ceiling", "floor mat", "person", "wall"], "prediction_id": "object_set_forecast::long_80f_stride40:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:0", "raw_prediction": "{\"object_set_forecast\":[\"person\",\"floor mat\",\"wall\",\"ceiling\"]}", "split": "test", "start_frame": 0, "target_future_id": "medium_40f_stride20:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:5", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["jigsaw puzzle", "puzzle piece"]}
+{"correct": 0, "end_frame": 39, "episode_id": "5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6", "future_end_frame": 139, "future_start_frame": 100, "id": "medium_40f_stride20:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:0", "predicted_value": ["bed", "box", "floor", "person", "pillow", "wall"], "prediction_id": "object_set_forecast::medium_40f_stride20:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:0", "raw_prediction": "{\"object_set_forecast\":[\"person\",\"bed\",\"pillow\",\"wall\",\"floor\",\"box\"]}", "split": "test", "start_frame": 0, "target_future_id": "medium_40f_stride20:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:5", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["jigsaw puzzle", "puzzle piece"]}
+{"correct": 0, "end_frame": 29, "episode_id": "5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6", "future_end_frame": 159, "future_start_frame": 120, "id": "dense_20f_stride10:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:1", "predicted_value": ["door", "floor", "hand", "light", "person", "phone", "wall"], "prediction_id": "object_set_forecast::dense_20f_stride10:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:1", "raw_prediction": "{\"object_set_forecast\":[\"person\",\"hand\",\"phone\",\"door\",\"wall\",\"floor\",\"light\"]}", "split": "test", "start_frame": 10, "target_future_id": "medium_40f_stride20:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:6", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["jigsaw puzzle", "puzzle piece"]}
+{"correct": 0, "end_frame": 39, "episode_id": "5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6", "future_end_frame": 159, "future_start_frame": 120, "id": "dense_20f_stride10:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:2", "predicted_value": ["door", "light", "mat", "person", "phone", "wall"], "prediction_id": "object_set_forecast::dense_20f_stride10:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:2", "raw_prediction": "{\"object_set_forecast\":[\"person\",\"phone\",\"door\",\"mat\",\"wall\",\"light\"]}", "split": "test", "start_frame": 20, "target_future_id": "medium_40f_stride20:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:6", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["jigsaw puzzle", "puzzle piece"]}
+{"correct": 0, "end_frame": 59, "episode_id": "5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6", "future_end_frame": 159, "future_start_frame": 120, "id": "medium_40f_stride20:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:1", "predicted_value": ["bed", "box", "person", "pillow"], "prediction_id": "object_set_forecast::medium_40f_stride20:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:1", "raw_prediction": "{\"object_set_forecast\":[\"person\",\"bed\",\"pillow\",\"box\"]}", "split": "test", "start_frame": 20, "target_future_id": "medium_40f_stride20:5399ef86-4df9-49bc-809f-8f4f92f9e659__ep6:qa:6", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["jigsaw puzzle", "puzzle piece"]}
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+{"correct": 0, "end_frame": 3459, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3579, "future_start_frame": 3540, "id": "dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:329", "predicted_value": ["cardboard", "hand", "pen", "scissors", "table"], "prediction_id": "object_set_forecast::dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:329", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"pen\",\"cardboard\",\"hand\",\"table\"]}", "split": "test", "start_frame": 3440, "target_future_id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:162", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler", "scissors"]}
+{"correct": 0, "end_frame": 3519, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3579, "future_start_frame": 3540, "id": "long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:71", "predicted_value": ["cardboard", "cardboard pieces", "glue gun", "pencil", "ruler", "scissors"], "prediction_id": "object_set_forecast::long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:71", "raw_prediction": "{\"object_set_forecast\":[\"cardboard\",\"scissors\",\"pencil\",\"ruler\",\"glue gun\",\"cardboard pieces\"]}", "split": "test", "start_frame": 3440, "target_future_id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:162", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler", "scissors"]}
+{"correct": 0, "end_frame": 3479, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3579, "future_start_frame": 3540, "id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:157", "predicted_value": ["cardboard", "hand", "pen", "scissors", "table"], "prediction_id": "object_set_forecast::medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:157", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"pen\",\"cardboard\",\"hand\",\"table\"]}", "split": "test", "start_frame": 3440, "target_future_id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:162", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler", "scissors"]}
+{"correct": 0, "end_frame": 3469, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3599, "future_start_frame": 3560, "id": "dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:330", "predicted_value": ["cardboard", "pen", "pile of cardboard", "ruler", "scissors"], "prediction_id": "object_set_forecast::dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:330", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"cardboard\",\"ruler\",\"pen\",\"pile of cardboard\"]}\n\nThe person is using scissors to cut a piece of cardboard, with a ruler and pen nearby. They are working on a white surface with a large pile of cardboard pieces. The action of cutting and the presence of tools suggest that the person will continue to cut more cardboard pieces in the future.", "split": "test", "start_frame": 3450, "target_future_id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:163", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3479, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3599, "future_start_frame": 3560, "id": "dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:331", "predicted_value": ["cardboard scraps", "glue stick", "pencil", "ruler", "scissors", "wooden pieces"], "prediction_id": "object_set_forecast::dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:331", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"glue stick\",\"wooden pieces\",\"pencil\",\"ruler\",\"cardboard scraps\"]}", "split": "test", "start_frame": 3460, "target_future_id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:163", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3499, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3599, "future_start_frame": 3560, "id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:158", "predicted_value": ["bowl", "box", "cardboard", "glue gun", "hand", "knife", "pen", "pencil", "ruler", "scissors", "table"], "prediction_id": "object_set_forecast::medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:158", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"cardboard\",\"hand\",\"table\",\"pencil\",\"ruler\",\"glue gun\",\"box\",\"pen\",\"knife\",\"bowl\"]}", "split": "test", "start_frame": 3460, "target_future_id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:163", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3489, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3619, "future_start_frame": 3580, "id": "dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:332", "predicted_value": ["box cutter", "cardboard", "hand", "pencil", "ruler", "scissors", "table"], "prediction_id": "object_set_forecast::dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:332", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"pencil\",\"ruler\",\"cardboard\",\"box cutter\",\"hand\",\"table\"]}", "split": "test", "start_frame": 3470, "target_future_id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:164", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3499, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3619, "future_start_frame": 3580, "id": "dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:333", "predicted_value": ["cardboard", "hand", "pencil", "ruler", "scissors", "table"], "prediction_id": "object_set_forecast::dense_20f_stride10:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:333", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"pencil\",\"ruler\",\"cardboard\",\"hand\",\"table\"]}", "split": "test", "start_frame": 3480, "target_future_id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:164", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3559, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3619, "future_start_frame": 3580, "id": "long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:72", "predicted_value": ["cardboard", "pen", "pencil", "ruler", "scissors"], "prediction_id": "object_set_forecast::long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:72", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"pencil\",\"cardboard\",\"ruler\",\"pen\"]}", "split": "test", "start_frame": 3480, "target_future_id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:164", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3519, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3619, "future_start_frame": 3580, "id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:159", "predicted_value": ["cardboard", "glue gun", "paper", "pen", "pile of paper", "ruler", "scissors"], "prediction_id": "object_set_forecast::medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:159", "raw_prediction": "{\"object_set_forecast\":[\"glue gun\",\"scissors\",\"ruler\",\"paper\",\"cardboard\",\"pen\",\"pile of paper\"]}\n\nNote: The \"pile of paper\" is likely a typo in the original context and should be \"pile of cardboard\" as the person is working with cardboard pieces.", "split": "test", "start_frame": 3480, "target_future_id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:164", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3539, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3639, "future_start_frame": 3600, "id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:160", "predicted_value": ["cardboard", "desk", "hand", "pen", "person", "scissors"], "prediction_id": "object_set_forecast::medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:160", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"pen\",\"cardboard\",\"desk\",\"hand\",\"person\"]}", "split": "test", "start_frame": 3500, "target_future_id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:165", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3599, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3659, "future_start_frame": 3620, "id": "long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:73", "predicted_value": ["cardboard", "glue gun", "pencil", "ruler", "scissors", "stack of cardboard"], "prediction_id": "object_set_forecast::long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:73", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"pencil\",\"cardboard\",\"ruler\",\"glue gun\",\"stack of cardboard\"]}\n\nNote: The \"stack of cardboard\" is included as it is the most prominent object set in the scene and is likely to remain active.", "split": "test", "start_frame": 3520, "target_future_id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:166", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3559, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3659, "future_start_frame": 3620, "id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:161", "predicted_value": ["cardboard", "cardboard pieces", "glue gun", "pen", "ruler", "scissors"], "prediction_id": "object_set_forecast::medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:161", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"pen\",\"cardboard\",\"ruler\",\"glue gun\",\"cardboard pieces\"]}", "split": "test", "start_frame": 3520, "target_future_id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:166", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3579, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3719, "future_start_frame": 3640, "id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:162", "predicted_value": ["cardboard", "cardboard pieces", "glue gun", "pencil", "ruler", "scissors"], "prediction_id": "object_set_forecast::medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:162", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"pencil\",\"cardboard\",\"ruler\",\"glue gun\",\"cardboard pieces\"]}", "split": "test", "start_frame": 3540, "target_future_id": "long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:76", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3639, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3759, "future_start_frame": 3680, "id": "long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:74", "predicted_value": ["box cutter", "cardboard", "pen", "ruler", "scissors"], "prediction_id": "object_set_forecast::long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:74", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"pen\",\"cardboard\",\"ruler\",\"box cutter\"]}", "split": "test", "start_frame": 3560, "target_future_id": "long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:77", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3599, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3759, "future_start_frame": 3680, "id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:163", "predicted_value": ["box cutter", "cardboard", "hand", "pen", "pile of cardboard", "ruler", "scissors", "table"], "prediction_id": "object_set_forecast::medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:163", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"pen\",\"cardboard\",\"hand\",\"table\",\"box cutter\",\"ruler\",\"pile of cardboard\"]}", "split": "test", "start_frame": 3560, "target_future_id": "long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:77", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3619, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3759, "future_start_frame": 3680, "id": "medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:164", "predicted_value": ["cardboard", "cardboard pieces", "glue gun", "pencil", "ruler", "scissors"], "prediction_id": "object_set_forecast::medium_40f_stride20:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:164", "raw_prediction": "{\"object_set_forecast\":[\"cardboard\",\"pencil\",\"ruler\",\"scissors\",\"glue gun\",\"cardboard pieces\"]}", "split": "test", "start_frame": 3580, "target_future_id": "long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:77", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
+{"correct": 0, "end_frame": 3679, "episode_id": "9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2", "future_end_frame": 3799, "future_start_frame": 3720, "id": "long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:75", "predicted_value": ["cardboard", "cardboard pieces", "glue gun", "pen", "ruler", "scissors"], "prediction_id": "object_set_forecast::long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:75", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"pen\",\"cardboard\",\"ruler\",\"glue gun\",\"cardboard pieces\"]}", "split": "test", "start_frame": 3600, "target_future_id": "long_80f_stride40:9c553886-83c5-4dc4-be5c-dcb269b3a771__ep2:qa:78", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["cardboard pieces", "marker", "ruler"]}
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"split": "test", "start_frame": 860, "target_future_id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:47", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "scissors", "smartphone"]}
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beads\",\"pile of beads", "split": "test", "start_frame": 870, "target_future_id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:48", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["blue fan craft piece", "craft pieces", "purple craft pieces", "scissors", "smartphone", "yellow craft pieces"]}
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"split": "test", "start_frame": 2160, "target_future_id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:223", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["paper scraps", "scissors", "smartphone", "table"]}
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+{"correct": 0, "end_frame": 2329, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 2429, "future_start_frame": 2410, "id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:226", "predicted_value": ["colorful rubber bands", "hand", "mobile phone", "person", "scissors", "table"], "prediction_id": "object_set_forecast::dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:226", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"mobile phone\",\"colorful rubber bands\",\"table\",\"hand\",\"person\"]}", "split": "test", "start_frame": 2310, "target_future_id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:235", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft materials", "purple paper strip", "scissors", "smartphone"]}
+{"correct": 0, "end_frame": 2339, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 2439, "future_start_frame": 2420, "id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:227", "predicted_value": ["blue paper", "hand", "mobile phone", "pen", "purple paper", "scissors", "table", "white paper", "yellow paper"], "prediction_id": "object_set_forecast::dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:227", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"mobile phone\",\"yellow paper\",\"purple paper\",\"blue paper\",\"white paper\",\"pen\",\"hand\",\"table\"]}", "split": "test", "start_frame": 2320, "target_future_id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:236", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft materials", "purple paper strip", "scissors", "smartphone"]}
+{"correct": 0, "end_frame": 2399, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 2439, "future_start_frame": 2420, "id": "long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:53", "predicted_value": ["blue paper", "box cutter", "cable", "colorful paper strips", "hand", "mobile phone", "pen", "scissors", "table", "white paper", "yellow paper"], "prediction_id": "object_set_forecast::long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:53", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"mobile phone\",\"yellow paper\",\"blue paper\",\"white paper\",\"colorful paper strips\",\"pen\",\"cable\",\"box cutter\",\"hand\",\"table\"]}", "split": "test", "start_frame": 2320, "target_future_id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:236", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft materials", "purple paper strip", "scissors", "smartphone"]}
+{"correct": 0, "end_frame": 2359, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 2439, "future_start_frame": 2420, "id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:111", "predicted_value": ["earphone", "face mask", "hand", "mobile phone", "rubber bands", "scissors", "table"], "prediction_id": "object_set_forecast::medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:111", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"mobile phone\",\"rubber bands\",\"table\",\"hand\",\"earphone\",\"face mask\"]}", "split": "test", "start_frame": 2320, "target_future_id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:236", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft materials", "purple paper strip", "scissors", "smartphone"]}
+{"correct": 0, "end_frame": 2349, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 2449, "future_start_frame": 2430, "id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:228", "predicted_value": ["earphones", "paper", "paper clips", "pen", "scissors", "smartphone"], "prediction_id": "object_set_forecast::dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:228", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"smartphone\",\"paper clips\",\"paper\",\"pen\",\"earphones\"]}", "split": "test", "start_frame": 2330, "target_future_id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:237", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft materials", "purple paper strip", "scissors", "smartphone"]}
+{"correct": 0, "end_frame": 2359, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 2459, "future_start_frame": 2440, "id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:229", "predicted_value": ["colorful beads", "mobile phone", "paper", "pen", "scissors", "string"], "prediction_id": "object_set_forecast::dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:229", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"mobile phone\",\"colorful beads\",\"string\",\"pen\",\"paper\"]}\n\nThe future object set forecast is based on the observed activity of stringing colorful beads, with the scissors, mobile phone, and pen visible on the table. The stringing action suggests continued manipulation of the beads and string, while the paper may be used for organization or as a base. The scissors and mobile phone are likely to remain on the table for potential use or as reference.", "split": "test", "start_frame": 2340, "target_future_id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:238", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft materials", "purple paper strip", "scissors", "smartphone"]}
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+{"correct": 0, "end_frame": 2369, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 2469, "future_start_frame": 2450, "id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:230", "predicted_value": ["blue paper", "hand", "mobile phone", "person", "purple beads", "scissors", "table", "white rope", "yellow beads"], "prediction_id": "object_set_forecast::dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:230", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"mobile phone\",\"yellow beads\",\"purple beads\",\"blue paper\",\"white rope\",\"hand\",\"table\",\"person\"]}", "split": "test", "start_frame": 2350, "target_future_id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:239", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft materials", "purple paper strip", "scissors", "smartphone"]}
+{"correct": 0, "end_frame": 2379, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 2479, "future_start_frame": 2460, "id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:231", "predicted_value": ["hand", "paper", "pen", "puzzle pieces", "scissors", "smartphone", "table"], "prediction_id": "object_set_forecast::dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:231", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"smartphone\",\"paper\",\"puzzle pieces\",\"pen\",\"hand\",\"table\"]}", "split": "test", "start_frame": 2360, "target_future_id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:240", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft materials", "purple paper strip", "scissors", "smartphone"]}
+{"correct": 0, "end_frame": 2399, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 2479, "future_start_frame": 2460, "id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:113", "predicted_value": ["craft material", "hand", "mobile phone", "paper", "pen", "scissors", "table"], "prediction_id": "object_set_forecast::medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:113", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"mobile phone\",\"paper\",\"craft material\",\"pen\",\"hand\",\"table\"]}", "split": "test", "start_frame": 2360, "target_future_id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:240", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft materials", "purple paper strip", "scissors", "smartphone"]}
+{"correct": 0, "end_frame": 2389, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 2489, "future_start_frame": 2470, "id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:232", "predicted_value": ["hand", "paper", "pen", "puzzle pieces", "scissors", "smartphone", "table"], "prediction_id": "object_set_forecast::dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:232", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"smartphone\",\"paper\",\"puzzle pieces\",\"pen\",\"hand\",\"table\"]}", "split": "test", "start_frame": 2370, "target_future_id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:241", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft materials", "purple paper strip", "scissors", "smartphone"]}
+{"correct": 0, "end_frame": 2399, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 2499, "future_start_frame": 2480, "id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:233", "predicted_value": ["colorful beads", "hand", "mobile phone", "person", "scissors", "string", "table"], "prediction_id": "object_set_forecast::dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:233", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"mobile phone\",\"string\",\"colorful beads\",\"table\",\"hand\",\"person\"]}", "split": "test", "start_frame": 2380, "target_future_id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:242", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft materials", "purple paper strip", "scissors", "smartphone"]}
+{"correct": 0, "end_frame": 2419, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 2519, "future_start_frame": 2500, "id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:234", "predicted_value": ["craft paper", "desk", "pen", "phone", "rubber bands", "scissors"], "prediction_id": "object_set_forecast::dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:234", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"phone\",\"craft paper\",\"rubber bands\",\"desk\",\"pen\"]}", "split": "test", "start_frame": 2400, "target_future_id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:244", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft materials", "purple paper strip", "scissors", "smartphone"]}
+{"correct": 0, "end_frame": 2479, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 2519, "future_start_frame": 2500, "id": "long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:54", "predicted_value": [], "prediction_id": "object_set_forecast::long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:54", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"smartphone\",\"paper\",\"pencil\",\"pen\",\"rubber bands\",\"hand\",\"earphone\",\"desk\",\"box\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"hand\",\"", 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+{"correct": 0, "end_frame": 3889, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4019, "future_start_frame": 3980, "id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:378", "predicted_value": ["colorful paper strips", "glue stick", "hand", "mobile phone", "person", "puzzle pieces", "scissors", "table", "yellow paper strips"], "prediction_id": "object_set_forecast::dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:378", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"colorful paper strips\",\"mobile phone\",\"glue stick\",\"yellow paper strips\",\"puzzle pieces\",\"hand\",\"table\",\"person\"]}", "split": "test", "start_frame": 3870, "target_future_id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:190", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "paper strips", "scissors", "smartphone", "star-shaped craft pieces", "table"]}
+{"correct": 0, "end_frame": 3899, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4019, "future_start_frame": 3980, "id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:379", "predicted_value": ["bracelet", "craft supplies", "hands", "pen", "phone", "rubber bands", "scissors", "table"], "prediction_id": "object_set_forecast::dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:379", "raw_prediction": "{\"object_set_forecast\":[\"rubber bands\", \"hands\", \"table\", \"scissors\", \"phone\", \"pen\", \"bracelet\", \"craft supplies\"]}", "split": "test", "start_frame": 3880, "target_future_id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:190", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "paper strips", "scissors", "smartphone", "star-shaped craft pieces", "table"]}
+{"correct": 0, "end_frame": 3959, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4019, "future_start_frame": 3980, "id": "long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:88", "predicted_value": ["box", "bracelet", "cable", "hand", "pen", "phone", "rubber bands", "scissors", "table"], "prediction_id": "object_set_forecast::long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:88", "raw_prediction": "{\"object_set_forecast\":[\"rubber bands\", \"scissors\", \"phone\", \"pen\", \"hand\", \"table\", \"bracelet\", \"box\", \"cable\"]}", "split": "test", "start_frame": 3880, "target_future_id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:190", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "paper strips", "scissors", "smartphone", "star-shaped craft pieces", "table"]}
+{"correct": 0, "end_frame": 3919, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4019, "future_start_frame": 3980, "id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:185", "predicted_value": ["paper strips", "pen", "phone", "scissors", "sticky notes"], "prediction_id": "object_set_forecast::medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:185", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"sticky notes\",\"pen\",\"phone\",\"paper strips\"]}", "split": "test", "start_frame": 3880, "target_future_id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:190", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "paper strips", "scissors", "smartphone", "star-shaped craft pieces", "table"]}
+{"correct": 0, "end_frame": 3909, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4039, "future_start_frame": 4000, "id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:380", "predicted_value": ["hands", "mask", "pen", "phone", "rubber bands", "scissors", "table"], "prediction_id": "object_set_forecast::dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:380", "raw_prediction": "{\"object_set_forecast\":[\"rubber bands\", \"hands\", \"table\", \"scissors\", \"phone\", \"pen\", \"mask\"]}", "split": "test", "start_frame": 3890, "target_future_id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:191", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "scissors", "smartphone", "table"]}
+{"correct": 0, "end_frame": 3919, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4039, "future_start_frame": 4000, "id": "dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:381", "predicted_value": ["colorful paper strips", "paper fan", "pen", "scissors", "smartphone"], "prediction_id": "object_set_forecast::dense_20f_stride10:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:381", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"colorful paper strips\",\"smartphone\",\"pen\",\"paper fan\"]}\n\nNote: The prediction is based on the current activity of folding paper strips into fan shapes, with the scissors and smartphone remaining on the table. The pen is also present and could be used for marking or drawing. The paper fans are the current output of the activity.", "split": "test", "start_frame": 3900, "target_future_id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:191", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "scissors", "smartphone", "table"]}
+{"correct": 0, "end_frame": 3939, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4039, "future_start_frame": 4000, "id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:186", "predicted_value": ["craft paper", "glue stick", "paper", "pen", "pencil", "scissors", "smartphone", "stickers"], "prediction_id": "object_set_forecast::medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:186", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"glue stick\",\"smartphone\",\"paper\",\"pencil\",\"craft paper\",\"stickers\",\"pen\"]}", "split": "test", "start_frame": 3900, "target_future_id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:191", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "scissors", "smartphone", "table"]}
+{"correct": 0, "end_frame": 3999, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4059, "future_start_frame": 4020, "id": "long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:89", "predicted_value": ["colorful paper strips", "glue stick", "scissors", "smartphone", "white table"], "prediction_id": "object_set_forecast::long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:89", "raw_prediction": "{\"object_set_forecast\":[\"colorful paper strips\",\"scissors\",\"glue stick\",\"smartphone\",\"white table\"]}", "split": "test", "start_frame": 3920, "target_future_id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:192", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "scissors", "smartphone", "table"]}
+{"correct": 0, "end_frame": 3959, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4059, "future_start_frame": 4020, "id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:187", "predicted_value": ["paper balls", "pen", "phone", "scissors", "sticky notes"], "prediction_id": "object_set_forecast::medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:187", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"sticky notes\",\"pen\",\"phone\",\"paper balls\"]}", "split": "test", "start_frame": 3920, "target_future_id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:192", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "scissors", "smartphone", "table"]}
+{"correct": 0, "end_frame": 3979, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4119, "future_start_frame": 4040, "id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:188", "predicted_value": ["black paper", "blue paper", "craft accent", "craft accessory", "craft animal", "craft aspect", "craft attribute", "craft bag", "craft ball", "craft beads", "craft bottle", "craft box", "craft building", "craft characteristic", "craft circle", "craft component", "craft cone", "craft container", "craft cube", "craft cylinder", "craft decoration", "craft design", "craft detail", "craft element", "craft ellipse", "craft embellishment", "craft feature", "craft flower", "craft fragment", "craft glue", "craft heart", "craft human", "craft item", "craft knife", "craft landscape", "craft leaf", "craft lump", "craft mat", "craft material", "craft motif", "craft ornament", "craft oval", "craft part", "craft pattern", "craft piece", "craft polygon", "craft prism", "craft property", "craft pyramid", "craft quadrilateral", "craft quality", "craft rectangle", "craft ruler", "craft scene", "craft section", "craft segment", "craft sheet", "craft slab", "craft slice", "craft sphere", "craft square", "craft star", "craft stick", "craft strip", "craft supply", "craft tool", "craft trait", "craft triangle", "craft tube", "craft vehicle", "pen", "phone", "scissors", "white paper", "yellow paper"], "prediction_id": "object_set_forecast::medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:188", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"phone\",\"craft beads\",\"craft mat\",\"yellow paper\",\"blue paper\",\"black paper\",\"white paper\",\"pen\",\"craft glue\",\"craft stick\",\"craft ruler\",\"craft knife\",\"craft box\",\"craft bag\",\"craft tube\",\"craft bottle\",\"craft container\",\"craft tool\",\"craft accessory\",\"craft decoration\",\"craft material\",\"craft supply\",\"craft item\",\"craft piece\",\"craft component\",\"craft element\",\"craft fragment\",\"craft part\",\"craft segment\",\"craft section\",\"craft slice\",\"craft strip\",\"craft sheet\",\"craft slab\",\"craft lump\",\"craft ball\",\"craft cube\",\"craft sphere\",\"craft cylinder\",\"craft cone\",\"craft pyramid\",\"craft prism\",\"craft polygon\",\"craft quadrilateral\",\"craft triangle\",\"craft rectangle\",\"craft square\",\"craft circle\",\"craft oval\",\"craft ellipse\",\"craft star\",\"craft heart\",\"craft flower\",\"craft leaf\",\"craft animal\",\"craft human\",\"craft vehicle\",\"craft building\",\"craft landscape\",\"craft scene\",\"craft pattern\",\"craft design\",\"craft motif\",\"craft ornament\",\"craft embellishment\",\"craft accent\",\"craft detail\",\"craft feature\",\"craft characteristic\",\"craft attribute\",\"craft quality\",\"craft property\",\"craft trait\",\"craft aspect\",\"craft element\",\"craft component\",\"craft part\",\"craft piece\",\"craft fragment\",\"craft section\",\"craft slice\",\"craft strip\",\"craft sheet\",\"craft slab\",\"craft lump\",\"craft ball\",\"craft cube\",\"craft sphere\",\"craft cylinder\",\"craft cone\",\"craft pyramid\",\"craft prism\",\"craft polygon\",\"craft quadrilateral\",\"craft triangle\",\"craft rectangle\",\"craft square\",\"craft circle\",\"craft oval\",\"craft ellipse\",\"craft star\",\"craft heart\",\"craft flower\",\"craft leaf\",\"craft animal\",\"craft human\",\"craft vehicle\",\"craft building\",\"craft landscape\",\"craft scene\",\"craft pattern\",\"craft design\",\"craft motif\",\"craft ornament\",\"craft embellishment\",\"craft accent\",\"craft detail\",\"craft feature\",\"craft characteristic\",\"craft attribute\",\"craft quality\",\"craft property\",\"craft trait\",\"craft aspect\"]}", "split": "test", "start_frame": 3940, "target_future_id": "long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:92", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "scissors", "smartphone", "table"]}
+{"correct": 0, "end_frame": 4039, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4159, "future_start_frame": 4080, "id": "long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:90", "predicted_value": ["hands", "pen", "phone", "pile of rubber bands", "rubber bands", "scissors", "table"], "prediction_id": "object_set_forecast::long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:90", "raw_prediction": "{\"object_set_forecast\":[\"rubber bands\",\"hands\",\"table\",\"scissors\",\"phone\",\"pen\",\"pile of rubber bands\"]}", "split": "test", "start_frame": 3960, "target_future_id": "long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:93", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "scissors", "smartphone", "table"]}
+{"correct": 0, "end_frame": 3999, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4159, "future_start_frame": 4080, "id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:189", "predicted_value": ["craft material", "hand", "paper", "pen", "phone", "scissors", "table"], "prediction_id": "object_set_forecast::medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:189", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"pen\",\"phone\",\"paper\",\"craft material\",\"hand\",\"table\"]}", "split": "test", "start_frame": 3960, "target_future_id": "long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:93", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "scissors", "smartphone", "table"]}
+{"correct": 0, "end_frame": 4019, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4159, "future_start_frame": 4080, "id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:190", "predicted_value": ["colorful rubber bands", "hand", "person", "scissors", "smartphone", "table"], "prediction_id": "object_set_forecast::medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:190", "raw_prediction": "{\"object_set_forecast\":[\"colorful rubber bands\", \"scissors\", \"smartphone\", \"table\", \"hand\", \"person\"]}", "split": "test", "start_frame": 3980, "target_future_id": "long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:93", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "scissors", "smartphone", "table"]}
+{"correct": 0, "end_frame": 4079, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4199, "future_start_frame": 4120, "id": "long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:91", "predicted_value": ["craft mat", "phone", "rubber bands", "scissors", "table"], "prediction_id": "object_set_forecast::long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:91", "raw_prediction": "{\"object_set_forecast\":[\"rubber bands\",\"table\",\"scissors\",\"phone\",\"craft mat\"]}", "split": "test", "start_frame": 4000, "target_future_id": "long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:94", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "scissors", "smartphone"]}
+{"correct": 0, "end_frame": 4039, "episode_id": "b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2", "future_end_frame": 4199, "future_start_frame": 4120, "id": "medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:191", "predicted_value": ["craft material", "hand", "mobile phone", "paper", "pen", "scissors", "table"], "prediction_id": "object_set_forecast::medium_40f_stride20:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:191", "raw_prediction": "{\"object_set_forecast\":[\"scissors\",\"mobile phone\",\"pen\",\"paper\",\"craft material\",\"hand\",\"table\"]}", "split": "test", "start_frame": 4000, "target_future_id": "long_80f_stride40:b9dd769b-e31a-4fdb-945e-5a60db6487b0__ep2:qa:94", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["craft pieces", "scissors", "smartphone"]}
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+{"correct": 0, "end_frame": 4979, "episode_id": "ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2", "future_end_frame": 5079, "future_start_frame": 5040, "id": "medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:241", "predicted_value": ["earphone", "paper", "pen", "phone", "water bottle"], "prediction_id": "object_set_forecast::medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:241", "raw_prediction": "{\"object_set_forecast\":[\"phone\",\"paper\",\"pen\",\"water bottle\",\"earphone\"]}", "split": "test", "start_frame": 4940, "target_future_id": "medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:246", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["adhesive strip", "paper cone", "puzzle box", "smartphone", "water bottle"]}
+{"correct": 0, "end_frame": 5039, "episode_id": "ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2", "future_end_frame": 5159, "future_start_frame": 5080, "id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:118", "predicted_value": ["bag", "beads", "bottle", "earphone", "paper", "pen", "phone", "string"], "prediction_id": "object_set_forecast::long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:118", "raw_prediction": "{\"object_set_forecast\":[\"phone\",\"beads\",\"string\",\"bottle\",\"bag\",\"pen\",\"paper\",\"earphone\"]}", "split": "test", "start_frame": 4960, "target_future_id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:121", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["adhesive strip", "paper cone", "puzzle box", "smartphone", "water bottle"]}
+{"correct": 0, "end_frame": 4999, "episode_id": "ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2", "future_end_frame": 5159, "future_start_frame": 5080, "id": "medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:242", "predicted_value": ["earbuds", "headphones", "paper", "pen", "phone", "ruler", "scissors", "sticky notes", "water bottle"], "prediction_id": "object_set_forecast::medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:242", "raw_prediction": "{\"object_set_forecast\":[\"phone\",\"paper\",\"pen\",\"water bottle\",\"earbuds\",\"scissors\",\"ruler\",\"sticky notes\",\"headphones\"]}", "split": "test", "start_frame": 4960, "target_future_id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:121", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["adhesive strip", "paper cone", "puzzle box", "smartphone", "water bottle"]}
+{"correct": 0, "end_frame": 5019, "episode_id": "ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2", "future_end_frame": 5159, "future_start_frame": 5080, "id": "medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:243", "predicted_value": ["beads", "box", "bracelet", "paper", "pen", "phone", "water bottle"], "prediction_id": "object_set_forecast::medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:243", "raw_prediction": "{\"object_set_forecast\":[\"phone\",\"beads\",\"pen\",\"water bottle\",\"paper\",\"box\",\"bracelet\"]}", "split": "test", "start_frame": 4980, "target_future_id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:121", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["adhesive strip", "paper cone", "puzzle box", "smartphone", "water bottle"]}
+{"correct": 0, "end_frame": 5079, "episode_id": "ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2", "future_end_frame": 5199, "future_start_frame": 5120, "id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:119", "predicted_value": ["beads", "earphone", "paper", "pen", "phone", "water bottle"], "prediction_id": "object_set_forecast::long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:119", "raw_prediction": "{\"object_set_forecast\":[\"phone\",\"beads\",\"pen\",\"water bottle\",\"paper\",\"earphone\"]}", "split": "test", "start_frame": 5000, "target_future_id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:122", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["adhesive strip", "paper cone", "puzzle box", "smartphone", "water bottle"]}
+{"correct": 0, "end_frame": 5039, "episode_id": "ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2", "future_end_frame": 5199, "future_start_frame": 5120, "id": "medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:244", "predicted_value": ["beads", "box", "bracelet", "chair", "desk", "earphone", "hand", "laptop", "paper", "pen", "person", "phone", "smartphone", "string", "water bottle"], "prediction_id": "object_set_forecast::medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:244", "raw_prediction": "{\"object_set_forecast\":[\"phone\",\"beads\",\"string\",\"water bottle\",\"smartphone\",\"bracelet\",\"box\",\"pen\",\"paper\",\"laptop\",\"earphone\",\"hand\",\"desk\",\"chair\",\"person\"]}", "split": "test", "start_frame": 5000, "target_future_id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:122", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["adhesive strip", "paper cone", "puzzle box", "smartphone", "water bottle"]}
+{"correct": 0, "end_frame": 5059, "episode_id": "ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2", "future_end_frame": 5199, "future_start_frame": 5120, "id": "medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:245", "predicted_value": ["bracelet", "paper", "pen", "phone", "water bottle"], "prediction_id": "object_set_forecast::medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:245", "raw_prediction": "{\"object_set_forecast\":[\"phone\",\"paper\",\"pen\",\"water bottle\",\"bracelet\"]}", "split": "test", "start_frame": 5020, "target_future_id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:122", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["adhesive strip", "paper cone", "puzzle box", "smartphone", "water bottle"]}
+{"correct": 0, "end_frame": 5119, "episode_id": "ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2", "future_end_frame": 5239, "future_start_frame": 5160, "id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:120", "predicted_value": ["earphone", "paper", "pen", "phone", "water bottle"], "prediction_id": "object_set_forecast::long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:120", "raw_prediction": "{\"object_set_forecast\":[\"phone\",\"paper\",\"pen\",\"water bottle\",\"earphone\"]}", "split": "test", "start_frame": 5040, "target_future_id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:123", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["adhesive strip", "paper cone"]}
+{"correct": 0, "end_frame": 5079, "episode_id": "ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2", "future_end_frame": 5239, "future_start_frame": 5160, "id": "medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:246", "predicted_value": ["bracelet", "earbuds", "paper", "pen", "phone", "sticky notes", "water bottle"], "prediction_id": "object_set_forecast::medium_40f_stride20:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:246", "raw_prediction": "{\"object_set_forecast\":[\"phone\",\"earbuds\",\"water bottle\",\"sticky notes\",\"pen\",\"paper\",\"bracelet\"]}", "split": "test", "start_frame": 5040, "target_future_id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:123", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["adhesive strip", "paper cone"]}
+{"correct": 0, "end_frame": 5159, "episode_id": "ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2", "future_end_frame": 5279, "future_start_frame": 5200, "id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:121", "predicted_value": ["beads", "bottle", "box", "chair", "person", "phone", "table"], "prediction_id": "object_set_forecast::long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:121", "raw_prediction": "{\"object_set_forecast\":[\"phone\",\"beads\",\"bottle\",\"box\",\"table\",\"chair\",\"person\"]}", "split": "test", "start_frame": 5080, "target_future_id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:124", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["adhesive strip", "paper cone"]}
+{"correct": 0, "end_frame": 5199, "episode_id": "ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2", "future_end_frame": 5319, "future_start_frame": 5240, "id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:122", "predicted_value": ["box", "bracelets", "cup", "earbuds", "flowers", "paper", "pen", "phone", "portable charger", "scissors", "water bottle"], "prediction_id": "object_set_forecast::long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:122", "raw_prediction": "{\"object_set_forecast\":[\"phone\",\"bracelets\",\"pen\",\"water bottle\",\"portable charger\",\"box\",\"flowers\",\"scissors\",\"paper\",\"cup\",\"earbuds\"]}", "split": "test", "start_frame": 5120, "target_future_id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:125", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["adhesive strip", "paper cone"]}
+{"correct": 0, "end_frame": 5239, "episode_id": "ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2", "future_end_frame": 5359, "future_start_frame": 5280, "id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:123", "predicted_value": ["beads", "bracelet", "paper", "pen", "phone", "water bottle"], "prediction_id": "object_set_forecast::long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:123", "raw_prediction": "{\"object_set_forecast\":[\"phone\",\"beads\",\"pen\",\"paper\",\"water bottle\",\"bracelet\"]}", "split": "test", "start_frame": 5160, "target_future_id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:126", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["adhesive strip", "paper cone"]}
+{"correct": 0, "end_frame": 5279, "episode_id": "ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2", "future_end_frame": 5399, "future_start_frame": 5320, "id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:124", "predicted_value": ["bracelet", "paper", "pen", "phone", "water bottle"], "prediction_id": "object_set_forecast::long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:124", "raw_prediction": "{\"object_set_forecast\":[\"phone\",\"bracelet\",\"paper\",\"pen\",\"water bottle\"]}", "split": "test", "start_frame": 5200, "target_future_id": "long_80f_stride40:ba18b7c1-21ff-45da-8452-41acce7fc8de__ep2:qa:127", "task_id": "object_set_forecast", "task_label": "Future Object-Set Forecasting", "true_value": ["adhesive strip", "paper cone"]}
diff --git a/results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/summary.json b/results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/summary.json
new file mode 100644
index 0000000000000000000000000000000000000000..a06758110c9019799850b724b4d264763428c1b4
--- /dev/null
+++ b/results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/summary.json
@@ -0,0 +1,35 @@
+{
+  "run_id": "xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z",
+  "shard_dirs": [
+    "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z_shard0",
+    "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z_shard1"
+  ],
+  "status": "pass",
+  "tasks": {
+    "long_horizon_next_action": {
+      "metric_key": "macro_f1",
+      "metrics_json": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/long_horizon_next_action/metrics.json",
+      "num_samples": 3951,
+      "primary_score": 0.0023356666867101906,
+      "task_label": "Long-Horizon Next-Action Forecasting",
+      "task_number": 13
+    },
+    "next_subtask_forecast": {
+      "metric_key": "macro_f1",
+      "metrics_json": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/next_subtask_forecast/metrics.json",
+      "num_samples": 3951,
+      "primary_score": 0.004206715978529301,
+      "task_label": "Long-Horizon Next-Subtask Forecasting",
+      "task_number": 14
+    },
+    "object_set_forecast": {
+      "metric_key": "micro_f1",
+      "metrics_json": "results/omni_finetune/xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z/object_set_forecast/metrics.json",
+      "num_samples": 3951,
+      "primary_score": 0.1659483964851402,
+      "task_label": "Future Object-Set Forecasting",
+      "task_number": 17
+    }
+  },
+  "title": "Qwen3-Omni v6 Future Task Probes"
+}
diff --git a/scripts/build_artifact_index.py b/scripts/build_artifact_index.py
index ef3456bc1ab56fce75f8006bfefc6df95f4fd00c..10081a5e2b90999efb9882fe7d48ad74483e96f7 100644
--- a/scripts/build_artifact_index.py
+++ b/scripts/build_artifact_index.py
@@ -15,6 +15,7 @@ from pathlib import Path
 
 ROOT = Path(__file__).resolve().parents[1]
 OUTPUT = ROOT / "docs/data/artifact_index.json"
+QWEN3_FUTURE_TASK_PROBE_RUN_ID = "xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z"
 
 ARTIFACTS = [
     {
@@ -1177,6 +1178,65 @@ def verified_public_package_artifacts() -> list[dict]:
     return artifacts
 
 
+def qwen3_future_task_probe_artifacts() -> list[dict]:
+    run_dir = ROOT / "results/omni_finetune" / QWEN3_FUTURE_TASK_PROBE_RUN_ID
+    if not run_dir.exists():
+        return []
+
+    artifacts: list[dict] = [
+        {
+            "id": "qwen3_future_task_probe_package",
+            "title": "Qwen3 v6 future-task probe package",
+            "path": run_dir.relative_to(ROOT).as_posix(),
+            "kind": "model_result",
+            "surface": "repo_hf",
+            "shows": (
+                "Two-shard Qwen3-Omni v6 inference probe for tasks 13, 14, "
+                "and 17, with public-safe metrics, predictions, progress logs, "
+                "and merge report."
+            ),
+        }
+    ]
+    for relative_path, kind, label in [
+        ("summary.json", "metrics_source", "merged summary"),
+        ("collection_validation.json", "publication_audit", "collection validation"),
+        ("RUN_REPORT.md", "scaleup_status", "run report"),
+        ("long_horizon_next_action/metrics.json", "metrics_source", "task 13 metrics"),
+        ("next_subtask_forecast/metrics.json", "metrics_source", "task 14 metrics"),
+        ("object_set_forecast/metrics.json", "metrics_source", "task 17 metrics"),
+    ]:
+        path = run_dir / relative_path
+        if path.exists():
+            artifacts.append(
+                {
+                    "id": f"qwen3_future_task_probe_{relative_path.replace('/', '_').replace('.', '_')}",
+                    "title": f"Qwen3 future-task probe {label}",
+                    "path": path.relative_to(ROOT).as_posix(),
+                    "kind": kind,
+                    "surface": "repo_hf",
+                    "shows": f"Public-safe {label} for {QWEN3_FUTURE_TASK_PROBE_RUN_ID}.",
+                }
+            )
+
+    launcher_log = (
+        ROOT
+        / "results/omni_finetune/deferred_launchers"
+        / f"{QWEN3_FUTURE_TASK_PROBE_RUN_ID}.launcher.log"
+    )
+    if launcher_log.exists():
+        artifacts.append(
+            {
+                "id": "qwen3_future_task_probe_launcher_log",
+                "title": "Qwen3 future-task probe launcher log",
+                "path": launcher_log.relative_to(ROOT).as_posix(),
+                "kind": "scaleup_status",
+                "surface": "repo_hf",
+                "shows": "Launch and merge log for the two-shard future-task probe.",
+            }
+        )
+    return artifacts
+
+
 def artifact_entry(item: dict) -> dict:
     path = ROOT / item["path"]
     entry = {
@@ -1199,6 +1259,7 @@ def artifact_entry(item: dict) -> dict:
 def main() -> int:
     artifacts = [dict(item) for item in ARTIFACTS]
     artifacts.extend(verified_public_package_artifacts())
+    artifacts.extend(qwen3_future_task_probe_artifacts())
     summary_path = ROOT / "results/episode_task_suite/summary_report.json"
     if summary_path.exists():
         summary = json.loads(summary_path.read_text(encoding="utf-8"))
diff --git a/scripts/sync_hf_publish_mirrors.py b/scripts/sync_hf_publish_mirrors.py
index 1779fb2c6017b5a4c928b2fa1d7caa2b480309c4..2af1912d112396d43d4eea1ea491b4a38d8a0433 100644
--- a/scripts/sync_hf_publish_mirrors.py
+++ b/scripts/sync_hf_publish_mirrors.py
@@ -388,6 +388,7 @@ def main() -> int:
         | set(parity.a100_128_metadata_result_files())
         | set(parity.a100_128_raw20_result_files())
         | set(parity.model_output_task_probe_result_files())
+        | set(parity.qwen3_future_task_probe_result_files())
     )
     for filename in result_files:
         src = ROOT / "results" / filename
diff --git a/scripts/validate_mirror_parity.py b/scripts/validate_mirror_parity.py
index 7efe850714c36bf4d2c621c2d84c46a6cef61358..45486d3dda88ce1d8cb14b6f9550e48d01f1e207 100644
--- a/scripts/validate_mirror_parity.py
+++ b/scripts/validate_mirror_parity.py
@@ -18,6 +18,7 @@ from pathlib import Path
 ROOT = Path(__file__).resolve().parents[1]
 DEFAULT_HF_ROOT = ROOT.parent / "hf_publish"
 DEFAULT_OUTPUT = ROOT / "docs/data/mirror_parity.json"
+QWEN3_FUTURE_TASK_PROBE_RUN_ID = "xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z"
 
 DATA_FILES = [
     "additional_development_directions.json",
@@ -374,6 +375,26 @@ def model_output_task_probe_result_files() -> list[str]:
     return sorted(files)
 
 
+def qwen3_future_task_probe_result_files() -> list[str]:
+    """Return public-safe Qwen3 future-task probe outputs from the shard run."""
+
+    result_root = ROOT / "results/omni_finetune" / QWEN3_FUTURE_TASK_PROBE_RUN_ID
+    files: list[str] = []
+    if result_root.exists():
+        for path in result_root.rglob("*"):
+            if path.is_file():
+                files.append(path.relative_to(ROOT / "results").as_posix())
+
+    launcher_log = (
+        ROOT
+        / "results/omni_finetune/deferred_launchers"
+        / f"{QWEN3_FUTURE_TASK_PROBE_RUN_ID}.launcher.log"
+    )
+    if launcher_log.is_file():
+        files.append(launcher_log.relative_to(ROOT / "results").as_posix())
+    return sorted(files)
+
+
 def parity_group(name: str, local_path: Path, mirrors: dict[str, Path], hf_root: Path) -> dict:
     local = file_record(local_path, hf_root)
     mirror_records = {surface: file_record(path, hf_root) for surface, path in mirrors.items()}
@@ -474,6 +495,7 @@ def build_report(hf_root: Path) -> dict:
         | set(a100_128_metadata_result_files())
         | set(a100_128_raw20_result_files())
         | set(model_output_task_probe_result_files())
+        | set(qwen3_future_task_probe_result_files())
     )
     for filename in result_files:
         groups.append(