cy0307 commited on 12 days ago

Commit

d712490

verified ·

1 Parent(s): a3929d0

Add files using upload-large-folder tool

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Files changed (28) hide show

data/artifact_index.json +6 -6
data/mirror_parity.json +81 -81
data/public_surface_qa.json +10 -10
data/publication_audit.json +3 -3
data/scope_claims_audit.json +1 -1
data/single_episode_explorer.json +1 -1
data/source_alignment_audit.json +1 -1
data/task_surface_integrity.json +144 -144
data/website_integrity.json +9 -9
docs/data/artifact_index.json +6 -6
docs/data/mirror_parity.json +81 -81
docs/data/public_surface_qa.json +10 -10
docs/data/publication_audit.json +3 -3
docs/data/scope_claims_audit.json +1 -1
docs/data/single_episode_explorer.json +1 -1
docs/data/source_alignment_audit.json +1 -1
docs/data/task_surface_integrity.json +144 -144
docs/data/website_integrity.json +9 -9
metrics/artifact_index.json +6 -6
metrics/mirror_parity.json +81 -81
metrics/public_surface_qa.json +10 -10
metrics/publication_audit.json +3 -3
metrics/scope_claims_audit.json +1 -1
metrics/single_episode_explorer.json +1 -1
metrics/source_alignment_audit.json +1 -1
metrics/task_surface_integrity.json +144 -144
metrics/website_integrity.json +9 -9
scripts/build_single_episode_explorer.py +8 -7

data/artifact_index.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
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@@ -340,8 +340,8 @@
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@@ -462,7 +462,7 @@
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@@ -841,7 +841,7 @@
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@@ -898,7 +898,7 @@
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       "shows": "Confirms prepared GitHub/HF Space/artifact/model mirrors share the same critical data, figure, website HTML, and validator files.",
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       "hash_policy": "existence_and_size_only"
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     {

 {
   "title": "Ropedia Xperience-10M Task Suite Artifact Index",
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   "status": "pass",
   "artifact_count": 164,
   "missing": [],
       "surface": "repo_hf",
       "shows": "Runs the owner-side Qwen3-Omni v6 one-sample reproduction smoke from a private staged model, adapter, JSONL, and exported media cache.",
       "exists": true,
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       "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
       "exists": true,
       "bytes": 4432,
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       "id": "source_alignment_validator",
       "shows": "Defines public reproduction commands, expected outputs, and non-reproducible scale-up boundaries.",
       "exists": true,
       "bytes": 9016,
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       "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": 550970,
       "hash_policy": "existence_and_size_only"
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data/mirror_parity.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
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-  "generated_at_utc": "2026-06-13T22:21:20+00:00",
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@@ -139,44 +139,44 @@
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@@ -825,44 +825,44 @@
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@@ -874,44 +874,44 @@
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@@ -1413,44 +1413,44 @@
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@@ -1462,44 +1462,44 @@
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-          "generated_at_utc": "2026-06-13T17:46:47+00:00"
         },
         "scale_up_status": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-13T17:46:50+00:00"
         },
         "publication_package": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-13T17:46:58+00:00"
         },
         "mirror_parity": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-13T17:47:14+00:00"
         },
         "live_publication": {
           "exists": true,
@@ -100,10 +100,10 @@
       "status": "pass",
       "reason": "Public copy should consistently present the project as Ropedia Xperience-10M, with the Qwen3-Omni scale-up status.",
       "marker_counts": {
-        "Ropedia Xperience-10M Task Suite": 15,
-        "Xperience-10M": 149,
         "12-task": 32,
-        "Qwen3-Omni": 140,
         "128-episode pilot": 1
       }
     },

 {
   "title": "Ropedia Xperience-10M Public Project Surface",
   "status": "pass",
+  "generated_at_utc": "2026-06-14T05:33:58+00:00",
   "scope": "Repo README, GitHub Pages HTML, Hugging Face Space card, artifact dataset card, and model card.",
   "checks": [
     {
         "website_integrity": {
           "exists": true,
           "status": "pass",
+          "generated_at_utc": "2026-06-14T05:33:22+00:00"
         },
         "rendered_site_check": {
           "exists": true,
         "task_surface_integrity": {
           "exists": true,
           "status": "pass",
+          "generated_at_utc": "2026-06-14T05:33:57+00:00"
         },
         "source_alignment": {
           "exists": true,
           "status": "pass",
+          "generated_at_utc": "2026-06-14T05:33:57+00:00"
         },
         "scale_up_status": {
           "exists": true,
           "status": "pass",
+          "generated_at_utc": "2026-06-13T22:21:34+00:00"
         },
         "publication_package": {
           "exists": true,
           "status": "pass",
+          "generated_at_utc": "2026-06-14T05:33:36+00:00"
         },
         "mirror_parity": {
           "exists": true,
           "status": "pass",
+          "generated_at_utc": "2026-06-13T22:21:20+00:00"
         },
         "live_publication": {
           "exists": true,
       "status": "pass",
       "reason": "Public copy should consistently present the project as Ropedia Xperience-10M, with the Qwen3-Omni scale-up status.",
       "marker_counts": {
+        "Ropedia Xperience-10M Task Suite": 16,
+        "Xperience-10M": 147,
         "12-task": 32,
+        "Qwen3-Omni": 141,
         "128-episode pilot": 1
       }
     },

data/publication_audit.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-13T22:21:50+00:00",
   "checks": [
     {
       "name": "required_publication_assets_present",
@@ -209,7 +209,7 @@
     "hf_artifact_bundle": {
       "root": "hf_publish/artifacts",
       "exists": true,
-      "file_count": 1747,
       "text_file_count": 744,
       "largest_file": {
         "path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
@@ -220,7 +220,7 @@
     "hf_model_bundle": {
       "root": "hf_publish/model",
       "exists": true,
-      "file_count": 2173,
       "text_file_count": 900,
       "largest_file": {
         "path": "pytorch_model.bin",

 {
   "status": "pass",
+  "generated_at_utc": "2026-06-14T05:39:25+00:00",
   "checks": [
     {
       "name": "required_publication_assets_present",
     "hf_artifact_bundle": {
       "root": "hf_publish/artifacts",
       "exists": true,
+      "file_count": 1749,
       "text_file_count": 744,
       "largest_file": {
         "path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
     "hf_model_bundle": {
       "root": "hf_publish/model",
       "exists": true,
+      "file_count": 2175,
       "text_file_count": 900,
       "largest_file": {
         "path": "pytorch_model.bin",

data/scope_claims_audit.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-13T22:21:34+00:00",
   "summary": {
     "qwen3_omni_verified_diagnostic_pilot": true,
     "dataset_manifest_num_episodes": 119,

 {
   "status": "pass",
+  "generated_at_utc": "2026-06-14T05:34:03+00:00",
   "summary": {
     "qwen3_omni_verified_diagnostic_pilot": true,
     "dataset_manifest_num_episodes": 119,

data/single_episode_explorer.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "meta": {
-    "generated_at": "2026-06-06T21:22:14.639673+00:00",
     "window_count": 1161,
     "feature_dim": 8546,
     "object_label_rows": 1161,

 {
   "meta": {
+    "generated_at": "2026-06-14T05:33:08.450198+00:00",
     "window_count": 1161,
     "feature_dim": 8546,
     "object_label_rows": 1161,

data/source_alignment_audit.json CHANGED Viewed

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Source Alignment Note",
   "status": "pass",
-  "generated_at_utc": "2026-06-13T21:56:28+00:00",
   "alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
   "alignment_summary": {
     "full_dataset_repo": "ropedia-ai/xperience-10m",

 {
   "title": "Ropedia Xperience-10M Source Alignment Note",
   "status": "pass",
+  "generated_at_utc": "2026-06-14T05:33:57+00:00",
   "alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
   "alignment_summary": {
     "full_dataset_repo": "ropedia-ai/xperience-10m",

data/task_surface_integrity.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-13T21:56:31+00:00",
   "summary": {
     "task_count": 12,
     "expected_task_count": 12,
@@ -64,15 +64,15 @@
       "observed": "timeline_action"
     },
     {
-      "name": "timeline_action: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Action Recognition",
       "raw_hits": []
     },
     {
-      "name": "timeline_action: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "20-frame multimodal window",
       "raw_hits": []
     },
     {
@@ -82,27 +82,27 @@
       "raw_hits": []
     },
     {
-      "name": "timeline_action: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Egocentric Action Recognition",
       "raw_hits": []
     },
     {
-      "name": "timeline_action: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Recognize the current manipulation action from synchronized visual, motion, inertial, pose, and annotation context.",
       "raw_hits": []
     },
     {
-      "name": "timeline_action: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "current action class",
       "raw_hits": []
     },
     {
-      "name": "timeline_action: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "window features -> action label builder -> classifier",
       "raw_hits": []
     },
     {
@@ -184,15 +184,15 @@
       "observed": "timeline_subtask"
     },
     {
-      "name": "timeline_subtask: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Procedure Step Recognition",
       "raw_hits": []
     },
     {
-      "name": "timeline_subtask: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "20-frame multimodal window",
       "raw_hits": []
     },
     {
@@ -202,27 +202,27 @@
       "raw_hits": []
     },
     {
-      "name": "timeline_subtask: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Temporal Subtask Recognition",
       "raw_hits": []
     },
     {
-      "name": "timeline_subtask: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Recognize the broader activity stage so fine actions become a readable procedure timeline.",
       "raw_hits": []
     },
     {
-      "name": "timeline_subtask: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "current procedure step",
       "raw_hits": []
     },
     {
-      "name": "timeline_subtask: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "window features -> subtask label builder -> classifier",
       "raw_hits": []
     },
     {
@@ -304,15 +304,15 @@
       "observed": "transition_detection"
     },
     {
-      "name": "transition_detection: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Action Boundary Detection",
       "raw_hits": []
     },
     {
-      "name": "transition_detection: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "current window with boundary target",
       "raw_hits": []
     },
     {
@@ -322,27 +322,27 @@
       "raw_hits": []
     },
     {
-      "name": "transition_detection: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Temporal Action Segmentation",
       "raw_hits": []
     },
     {
-      "name": "transition_detection: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Detect the local moment where the episode changes from one action segment to the next.",
       "raw_hits": []
     },
     {
-      "name": "transition_detection: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "boundary or steady",
       "raw_hits": []
     },
     {
-      "name": "transition_detection: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "action changes -> boundary labels -> binary classifier",
       "raw_hits": []
     },
     {
@@ -422,15 +422,15 @@
       "observed": "next_action"
     },
     {
-      "name": "next_action: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Next-Action Prediction",
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "current window at time t",
       "raw_hits": []
     },
     {
@@ -440,27 +440,27 @@
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Short-Horizon Intention Prediction",
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Forecast the near-future action from the current observations only.",
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "action at t+20 frames",
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "current features -> future label shift -> classifier",
       "raw_hits": []
     },
     {
@@ -540,15 +540,15 @@
       "observed": "hand_trajectory_forecast"
     },
     {
-      "name": "hand_trajectory_forecast: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Hand Trajectory Forecasting",
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "current multimodal window",
       "raw_hits": []
     },
     {
@@ -558,27 +558,27 @@
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "3D Hand Motion Forecasting",
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Predict the future 3D left/right hand path from the current multimodal state.",
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "future hand-joint trajectory",
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "current features -> future mocap target -> regression head",
       "raw_hits": []
     },
     {
@@ -658,15 +658,15 @@
       "observed": "contact_prediction"
     },
     {
-      "name": "contact_prediction: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Contact State Prediction",
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "non-contact, non-caption features",
       "raw_hits": []
     },
     {
@@ -676,27 +676,27 @@
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Human-Object Contact Prediction",
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Predict whether body or hand contact with the scene is occurring without leaking contact labels.",
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "contact or no contact",
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "feature filter -> contact target -> binary classifier",
       "raw_hits": []
     },
     {
@@ -774,15 +774,15 @@
       "observed": "object_relevance"
     },
     {
-      "name": "object_relevance: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Object Relevance Prediction",
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "non-caption multimodal features",
       "raw_hits": []
     },
     {
@@ -792,27 +792,27 @@
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Object-Centric Interaction Recognition",
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Infer which objects are relevant to the current manipulation window from non-caption features.",
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "relevant object set",
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "object vocabulary -> multi-hot labels -> sigmoid heads",
       "raw_hits": []
     },
     {
@@ -892,15 +892,15 @@
       "observed": "caption_grounding"
     },
     {
-      "name": "caption_grounding: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Language Grounding",
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "text-like query and candidate windows",
       "raw_hits": []
     },
     {
@@ -910,27 +910,27 @@
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Language-to-Moment Grounding",
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Retrieve the matching time window for an annotation-derived text query.",
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "ranked matching moments",
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "query features -> candidate index -> cosine ranker",
       "raw_hits": []
     },
     {
@@ -1008,15 +1008,15 @@
       "observed": "cross_modal_retrieval"
     },
     {
-      "name": "cross_modal_retrieval: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Cross-Modal Retrieval",
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "motion/IMU/pose query; depth/video candidates",
       "raw_hits": []
     },
     {
@@ -1026,27 +1026,27 @@
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Multimodal Representation Retrieval",
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Use motion, IMU, and camera-pose signals to retrieve the matching depth/video window.",
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "ranked visual windows",
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "modality split -> projection -> nearest-neighbor ranker",
       "raw_hits": []
     },
     {
@@ -1126,15 +1126,15 @@
       "observed": "modality_reconstruction"
     },
     {
-      "name": "modality_reconstruction: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Cross-Modal Reconstruction",
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "motion, IMU, and camera/pose features",
       "raw_hits": []
     },
     {
@@ -1144,27 +1144,27 @@
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Modality Feature Reconstruction",
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Predict compressed depth/video feature vectors from motion, IMU, and camera-pose features.",
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "reconstructed depth/video vector",
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "source-target split -> scaler -> regression head",
       "raw_hits": []
     },
     {
@@ -1244,15 +1244,15 @@
       "observed": "temporal_order"
     },
     {
-      "name": "temporal_order: public_field_display_name_is_human_readable",
       "status": "pass",
       "value": "Temporal Order Verification",
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "two adjacent windows plus difference vector",
       "raw_hits": []
     },
     {
@@ -1262,27 +1262,27 @@
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Temporal Order Verification",
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Tell whether two neighboring windows are in chronological order or reversed.",
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "correct or reversed",
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "pair builder -> feature combiner -> binary classifier",
       "raw_hits": []
     },
     {
@@ -1360,15 +1360,15 @@
       "observed": "misalignment_detection"
     },
     {
-      "name": "misalignment_detection: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Multimodal Synchronization Detection",
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "motion-side and visual/depth-side feature groups",
       "raw_hits": []
     },
     {
@@ -1378,27 +1378,27 @@
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Cross-Modal Misalignment Detection",
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Detect whether motion and visual/depth streams have been artificially shifted out of sync.",
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "aligned or shifted",
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "aligned/shifted pairs -> feature combiner -> binary classifier",
       "raw_hits": []
     },
     {

 {
   "status": "pass",
+  "generated_at_utc": "2026-06-14T05:33:57+00:00",
   "summary": {
     "task_count": 12,
     "expected_task_count": 12,
       "observed": "timeline_action"
     },
     {
+      "name": "timeline_action: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Egocentric Action Recognition",
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "window features -> action label builder -> classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "current action class",
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "20-frame multimodal window",
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Action Recognition",
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Recognize the current manipulation action from synchronized visual, motion, inertial, pose, and annotation context.",
       "raw_hits": []
     },
     {
       "observed": "timeline_subtask"
     },
     {
+      "name": "timeline_subtask: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Temporal Subtask Recognition",
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "window features -> subtask label builder -> classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "current procedure step",
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "20-frame multimodal window",
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Procedure Step Recognition",
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Recognize the broader activity stage so fine actions become a readable procedure timeline.",
       "raw_hits": []
     },
     {
       "observed": "transition_detection"
     },
     {
+      "name": "transition_detection: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Temporal Action Segmentation",
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "action changes -> boundary labels -> binary classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "boundary or steady",
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "current window with boundary target",
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Action Boundary Detection",
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Detect the local moment where the episode changes from one action segment to the next.",
       "raw_hits": []
     },
     {
       "observed": "next_action"
     },
     {
+      "name": "next_action: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Short-Horizon Intention Prediction",
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "current features -> future label shift -> classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "action at t+20 frames",
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "current window at time t",
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Next-Action Prediction",
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Forecast the near-future action from the current observations only.",
       "raw_hits": []
     },
     {
       "observed": "hand_trajectory_forecast"
     },
     {
+      "name": "hand_trajectory_forecast: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "3D Hand Motion Forecasting",
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "current features -> future mocap target -> regression head",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "future hand-joint trajectory",
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "current multimodal window",
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Hand Trajectory Forecasting",
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Predict the future 3D left/right hand path from the current multimodal state.",
       "raw_hits": []
     },
     {
       "observed": "contact_prediction"
     },
     {
+      "name": "contact_prediction: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Human-Object Contact Prediction",
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "feature filter -> contact target -> binary classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "contact or no contact",
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "non-contact, non-caption features",
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Contact State Prediction",
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Predict whether body or hand contact with the scene is occurring without leaking contact labels.",
       "raw_hits": []
     },
     {
       "observed": "object_relevance"
     },
     {
+      "name": "object_relevance: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Object-Centric Interaction Recognition",
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "object vocabulary -> multi-hot labels -> sigmoid heads",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "relevant object set",
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "non-caption multimodal features",
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Object Relevance Prediction",
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Infer which objects are relevant to the current manipulation window from non-caption features.",
       "raw_hits": []
     },
     {
       "observed": "caption_grounding"
     },
     {
+      "name": "caption_grounding: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Language-to-Moment Grounding",
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "query features -> candidate index -> cosine ranker",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "ranked matching moments",
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "text-like query and candidate windows",
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Language Grounding",
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Retrieve the matching time window for an annotation-derived text query.",
       "raw_hits": []
     },
     {
       "observed": "cross_modal_retrieval"
     },
     {
+      "name": "cross_modal_retrieval: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Multimodal Representation Retrieval",
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "modality split -> projection -> nearest-neighbor ranker",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "ranked visual windows",
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "motion/IMU/pose query; depth/video candidates",
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Cross-Modal Retrieval",
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Use motion, IMU, and camera-pose signals to retrieve the matching depth/video window.",
       "raw_hits": []
     },
     {
       "observed": "modality_reconstruction"
     },
     {
+      "name": "modality_reconstruction: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Modality Feature Reconstruction",
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "source-target split -> scaler -> regression head",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "reconstructed depth/video vector",
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "motion, IMU, and camera/pose features",
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Cross-Modal Reconstruction",
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Predict compressed depth/video feature vectors from motion, IMU, and camera-pose features.",
       "raw_hits": []
     },
     {
       "observed": "temporal_order"
     },
     {
+      "name": "temporal_order: public_field_research_name_is_human_readable",
       "status": "pass",
       "value": "Temporal Order Verification",
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "pair builder -> feature combiner -> binary classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "correct or reversed",
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "two adjacent windows plus difference vector",
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Temporal Order Verification",
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Tell whether two neighboring windows are in chronological order or reversed.",
       "raw_hits": []
     },
     {
       "observed": "misalignment_detection"
     },
     {
+      "name": "misalignment_detection: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Cross-Modal Misalignment Detection",
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "aligned/shifted pairs -> feature combiner -> binary classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "aligned or shifted",
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "motion-side and visual/depth-side feature groups",
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Multimodal Synchronization Detection",
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Detect whether motion and visual/depth streams have been artificially shifted out of sync.",
       "raw_hits": []
     },
     {

data/website_integrity.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-13T21:56:42+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
@@ -74,8 +74,8 @@
       "name": "project_overview_precedes_progress_ledger",
       "status": "pass",
       "reason": "The project overview should appear before the deeper progress ledger.",
-      "overview_index": 67412,
-      "evidence_index": 93059
     },
     {
       "name": "project_status_links_json",
@@ -153,9 +153,9 @@
       "name": "evaluation_protocol_between_overview_and_progress",
       "status": "pass",
       "reason": "The evaluation protocol should appear before the deeper evidence ledger.",
-      "overview_index": 67412,
-      "protocol_index": 89241,
-      "evidence_index": 93059
     },
     {
       "name": "evaluation_protocol_links_json",
@@ -167,7 +167,7 @@
       "name": "visual_figures_link_task_suite_image",
       "status": "pass",
       "reason": "The website should expose the main task-suite figure.",
-      "marker_count": 3
     },
     {
       "name": "suite_task_map_precedes_modality_atlas",
@@ -253,7 +253,7 @@
     },
     {
       "path": "data/artifact_index.json",
-      "bytes": 88913,
       "top_level_type": "dict"
     },
     {
@@ -293,7 +293,7 @@
     },
     {
       "path": "data/mirror_parity.json",
-      "bytes": 548190,
       "top_level_type": "dict"
     },
     {

 {
   "status": "pass",
+  "generated_at_utc": "2026-06-14T05:39:07+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
       "name": "project_overview_precedes_progress_ledger",
       "status": "pass",
       "reason": "The project overview should appear before the deeper progress ledger.",
+      "overview_index": 70501,
+      "evidence_index": 96148
     },
     {
       "name": "project_status_links_json",
       "name": "evaluation_protocol_between_overview_and_progress",
       "status": "pass",
       "reason": "The evaluation protocol should appear before the deeper evidence ledger.",
+      "overview_index": 70501,
+      "protocol_index": 92330,
+      "evidence_index": 96148
     },
     {
       "name": "evaluation_protocol_links_json",
       "name": "visual_figures_link_task_suite_image",
       "status": "pass",
       "reason": "The website should expose the main task-suite figure.",
+      "marker_count": 5
     },
     {
       "name": "suite_task_map_precedes_modality_atlas",
     },
     {
       "path": "data/artifact_index.json",
+      "bytes": 89995,
       "top_level_type": "dict"
     },
     {
     },
     {
       "path": "data/mirror_parity.json",
+      "bytes": 550970,
       "top_level_type": "dict"
     },
     {

docs/data/artifact_index.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "title": "Ropedia Xperience-10M Task Suite Artifact Index",
-  "generated_at_utc": "2026-06-13T21:57:03+00:00",
   "status": "pass",
   "artifact_count": 164,
   "missing": [],
@@ -340,8 +340,8 @@
       "surface": "repo_hf",
       "shows": "Runs the owner-side Qwen3-Omni v6 one-sample reproduction smoke from a private staged model, adapter, JSONL, and exported media cache.",
       "exists": true,
-      "bytes": 2514,
-      "sha256": "65c692efa70e4440041bb4c1b7da2d92eded6b2925a22889caa1a18621e59247"
     },
     {
       "id": "qwen3_video_feature_compat_patch",
@@ -462,7 +462,7 @@
       "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
       "exists": true,
       "bytes": 4432,
-      "sha256": "b7f30209e242dd07a0a5de5154a0c8caf3d8988995591da2bd35ba5bce0aa4b8"
     },
     {
       "id": "source_alignment_validator",
@@ -841,7 +841,7 @@
       "shows": "Defines public reproduction commands, expected outputs, and non-reproducible scale-up boundaries.",
       "exists": true,
       "bytes": 9016,
-      "sha256": "765cd4e45e0844534839cc9bcfe473613fa76c2aa073c74ccb08ac15a51da197"
     },
     {
       "id": "reproducibility_matrix",
@@ -898,7 +898,7 @@
       "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": 548190,
       "hash_policy": "existence_and_size_only"
     },
     {

 {
   "title": "Ropedia Xperience-10M Task Suite Artifact Index",
+  "generated_at_utc": "2026-06-14T05:39:44+00:00",
   "status": "pass",
   "artifact_count": 164,
   "missing": [],
       "surface": "repo_hf",
       "shows": "Runs the owner-side Qwen3-Omni v6 one-sample reproduction smoke from a private staged model, adapter, JSONL, and exported media cache.",
       "exists": true,
+      "bytes": 4082,
+      "sha256": "23cdd97be6cc7f516d231f65646215ff7447f47243040920b1840c7e76c09ff1"
     },
     {
       "id": "qwen3_video_feature_compat_patch",
       "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
       "exists": true,
       "bytes": 4432,
+      "sha256": "24076a6db867af49f9b82d24b68816a1d2bbb4b31f7031aa89699326cb33539b"
     },
     {
       "id": "source_alignment_validator",
       "shows": "Defines public reproduction commands, expected outputs, and non-reproducible scale-up boundaries.",
       "exists": true,
       "bytes": 9016,
+      "sha256": "c1b9c7bd3fdd7446f41b1c4247727ce135697bfc3539b82cabd0d0c09fe7307f"
     },
     {
       "id": "reproducibility_matrix",
       "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": 550970,
       "hash_policy": "existence_and_size_only"
     },
     {

docs/data/mirror_parity.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-13T22:21:20+00:00",
   "hf_root": "hf_publish",
   "summary": {
     "group_count": 369,
@@ -139,44 +139,44 @@
         "path": "repo:docs/data/artifact_index.json",
         "exists": true,
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 {
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-    "generated_at": "2026-06-06T21:22:14.639673+00:00",
     "window_count": 1161,
     "feature_dim": 8546,
     "object_label_rows": 1161,

 {
   "meta": {
+    "generated_at": "2026-06-14T05:33:08.450198+00:00",
     "window_count": 1161,
     "feature_dim": 8546,
     "object_label_rows": 1161,

docs/data/source_alignment_audit.json CHANGED Viewed

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Source Alignment Note",
   "status": "pass",
-  "generated_at_utc": "2026-06-13T21:56:28+00:00",
   "alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
   "alignment_summary": {
     "full_dataset_repo": "ropedia-ai/xperience-10m",

 {
   "title": "Ropedia Xperience-10M Source Alignment Note",
   "status": "pass",
+  "generated_at_utc": "2026-06-14T05:33:57+00:00",
   "alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
   "alignment_summary": {
     "full_dataset_repo": "ropedia-ai/xperience-10m",

docs/data/task_surface_integrity.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-13T21:56:31+00:00",
   "summary": {
     "task_count": 12,
     "expected_task_count": 12,
@@ -64,15 +64,15 @@
       "observed": "timeline_action"
     },
     {
-      "name": "timeline_action: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Action Recognition",
       "raw_hits": []
     },
     {
-      "name": "timeline_action: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "20-frame multimodal window",
       "raw_hits": []
     },
     {
@@ -82,27 +82,27 @@
       "raw_hits": []
     },
     {
-      "name": "timeline_action: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Egocentric Action Recognition",
       "raw_hits": []
     },
     {
-      "name": "timeline_action: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Recognize the current manipulation action from synchronized visual, motion, inertial, pose, and annotation context.",
       "raw_hits": []
     },
     {
-      "name": "timeline_action: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "current action class",
       "raw_hits": []
     },
     {
-      "name": "timeline_action: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "window features -> action label builder -> classifier",
       "raw_hits": []
     },
     {
@@ -184,15 +184,15 @@
       "observed": "timeline_subtask"
     },
     {
-      "name": "timeline_subtask: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Procedure Step Recognition",
       "raw_hits": []
     },
     {
-      "name": "timeline_subtask: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "20-frame multimodal window",
       "raw_hits": []
     },
     {
@@ -202,27 +202,27 @@
       "raw_hits": []
     },
     {
-      "name": "timeline_subtask: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Temporal Subtask Recognition",
       "raw_hits": []
     },
     {
-      "name": "timeline_subtask: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Recognize the broader activity stage so fine actions become a readable procedure timeline.",
       "raw_hits": []
     },
     {
-      "name": "timeline_subtask: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "current procedure step",
       "raw_hits": []
     },
     {
-      "name": "timeline_subtask: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "window features -> subtask label builder -> classifier",
       "raw_hits": []
     },
     {
@@ -304,15 +304,15 @@
       "observed": "transition_detection"
     },
     {
-      "name": "transition_detection: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Action Boundary Detection",
       "raw_hits": []
     },
     {
-      "name": "transition_detection: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "current window with boundary target",
       "raw_hits": []
     },
     {
@@ -322,27 +322,27 @@
       "raw_hits": []
     },
     {
-      "name": "transition_detection: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Temporal Action Segmentation",
       "raw_hits": []
     },
     {
-      "name": "transition_detection: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Detect the local moment where the episode changes from one action segment to the next.",
       "raw_hits": []
     },
     {
-      "name": "transition_detection: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "boundary or steady",
       "raw_hits": []
     },
     {
-      "name": "transition_detection: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "action changes -> boundary labels -> binary classifier",
       "raw_hits": []
     },
     {
@@ -422,15 +422,15 @@
       "observed": "next_action"
     },
     {
-      "name": "next_action: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Next-Action Prediction",
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "current window at time t",
       "raw_hits": []
     },
     {
@@ -440,27 +440,27 @@
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Short-Horizon Intention Prediction",
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Forecast the near-future action from the current observations only.",
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "action at t+20 frames",
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "current features -> future label shift -> classifier",
       "raw_hits": []
     },
     {
@@ -540,15 +540,15 @@
       "observed": "hand_trajectory_forecast"
     },
     {
-      "name": "hand_trajectory_forecast: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Hand Trajectory Forecasting",
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "current multimodal window",
       "raw_hits": []
     },
     {
@@ -558,27 +558,27 @@
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "3D Hand Motion Forecasting",
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Predict the future 3D left/right hand path from the current multimodal state.",
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "future hand-joint trajectory",
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "current features -> future mocap target -> regression head",
       "raw_hits": []
     },
     {
@@ -658,15 +658,15 @@
       "observed": "contact_prediction"
     },
     {
-      "name": "contact_prediction: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Contact State Prediction",
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "non-contact, non-caption features",
       "raw_hits": []
     },
     {
@@ -676,27 +676,27 @@
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Human-Object Contact Prediction",
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Predict whether body or hand contact with the scene is occurring without leaking contact labels.",
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "contact or no contact",
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "feature filter -> contact target -> binary classifier",
       "raw_hits": []
     },
     {
@@ -774,15 +774,15 @@
       "observed": "object_relevance"
     },
     {
-      "name": "object_relevance: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Object Relevance Prediction",
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "non-caption multimodal features",
       "raw_hits": []
     },
     {
@@ -792,27 +792,27 @@
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Object-Centric Interaction Recognition",
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Infer which objects are relevant to the current manipulation window from non-caption features.",
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "relevant object set",
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "object vocabulary -> multi-hot labels -> sigmoid heads",
       "raw_hits": []
     },
     {
@@ -892,15 +892,15 @@
       "observed": "caption_grounding"
     },
     {
-      "name": "caption_grounding: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Language Grounding",
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "text-like query and candidate windows",
       "raw_hits": []
     },
     {
@@ -910,27 +910,27 @@
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Language-to-Moment Grounding",
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Retrieve the matching time window for an annotation-derived text query.",
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "ranked matching moments",
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "query features -> candidate index -> cosine ranker",
       "raw_hits": []
     },
     {
@@ -1008,15 +1008,15 @@
       "observed": "cross_modal_retrieval"
     },
     {
-      "name": "cross_modal_retrieval: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Cross-Modal Retrieval",
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "motion/IMU/pose query; depth/video candidates",
       "raw_hits": []
     },
     {
@@ -1026,27 +1026,27 @@
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Multimodal Representation Retrieval",
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Use motion, IMU, and camera-pose signals to retrieve the matching depth/video window.",
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "ranked visual windows",
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "modality split -> projection -> nearest-neighbor ranker",
       "raw_hits": []
     },
     {
@@ -1126,15 +1126,15 @@
       "observed": "modality_reconstruction"
     },
     {
-      "name": "modality_reconstruction: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Cross-Modal Reconstruction",
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "motion, IMU, and camera/pose features",
       "raw_hits": []
     },
     {
@@ -1144,27 +1144,27 @@
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Modality Feature Reconstruction",
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Predict compressed depth/video feature vectors from motion, IMU, and camera-pose features.",
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "reconstructed depth/video vector",
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "source-target split -> scaler -> regression head",
       "raw_hits": []
     },
     {
@@ -1244,15 +1244,15 @@
       "observed": "temporal_order"
     },
     {
-      "name": "temporal_order: public_field_display_name_is_human_readable",
       "status": "pass",
       "value": "Temporal Order Verification",
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "two adjacent windows plus difference vector",
       "raw_hits": []
     },
     {
@@ -1262,27 +1262,27 @@
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Temporal Order Verification",
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Tell whether two neighboring windows are in chronological order or reversed.",
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "correct or reversed",
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "pair builder -> feature combiner -> binary classifier",
       "raw_hits": []
     },
     {
@@ -1360,15 +1360,15 @@
       "observed": "misalignment_detection"
     },
     {
-      "name": "misalignment_detection: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Multimodal Synchronization Detection",
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "motion-side and visual/depth-side feature groups",
       "raw_hits": []
     },
     {
@@ -1378,27 +1378,27 @@
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Cross-Modal Misalignment Detection",
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Detect whether motion and visual/depth streams have been artificially shifted out of sync.",
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "aligned or shifted",
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "aligned/shifted pairs -> feature combiner -> binary classifier",
       "raw_hits": []
     },
     {

 {
   "status": "pass",
+  "generated_at_utc": "2026-06-14T05:33:57+00:00",
   "summary": {
     "task_count": 12,
     "expected_task_count": 12,
       "observed": "timeline_action"
     },
     {
+      "name": "timeline_action: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Egocentric Action Recognition",
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "window features -> action label builder -> classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "current action class",
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "20-frame multimodal window",
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Action Recognition",
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Recognize the current manipulation action from synchronized visual, motion, inertial, pose, and annotation context.",
       "raw_hits": []
     },
     {
       "observed": "timeline_subtask"
     },
     {
+      "name": "timeline_subtask: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Temporal Subtask Recognition",
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "window features -> subtask label builder -> classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "current procedure step",
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "20-frame multimodal window",
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Procedure Step Recognition",
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Recognize the broader activity stage so fine actions become a readable procedure timeline.",
       "raw_hits": []
     },
     {
       "observed": "transition_detection"
     },
     {
+      "name": "transition_detection: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Temporal Action Segmentation",
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "action changes -> boundary labels -> binary classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "boundary or steady",
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "current window with boundary target",
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Action Boundary Detection",
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Detect the local moment where the episode changes from one action segment to the next.",
       "raw_hits": []
     },
     {
       "observed": "next_action"
     },
     {
+      "name": "next_action: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Short-Horizon Intention Prediction",
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "current features -> future label shift -> classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "action at t+20 frames",
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "current window at time t",
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Next-Action Prediction",
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Forecast the near-future action from the current observations only.",
       "raw_hits": []
     },
     {
       "observed": "hand_trajectory_forecast"
     },
     {
+      "name": "hand_trajectory_forecast: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "3D Hand Motion Forecasting",
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "current features -> future mocap target -> regression head",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "future hand-joint trajectory",
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "current multimodal window",
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Hand Trajectory Forecasting",
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Predict the future 3D left/right hand path from the current multimodal state.",
       "raw_hits": []
     },
     {
       "observed": "contact_prediction"
     },
     {
+      "name": "contact_prediction: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Human-Object Contact Prediction",
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "feature filter -> contact target -> binary classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "contact or no contact",
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "non-contact, non-caption features",
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Contact State Prediction",
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Predict whether body or hand contact with the scene is occurring without leaking contact labels.",
       "raw_hits": []
     },
     {
       "observed": "object_relevance"
     },
     {
+      "name": "object_relevance: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Object-Centric Interaction Recognition",
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "object vocabulary -> multi-hot labels -> sigmoid heads",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "relevant object set",
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "non-caption multimodal features",
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Object Relevance Prediction",
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Infer which objects are relevant to the current manipulation window from non-caption features.",
       "raw_hits": []
     },
     {
       "observed": "caption_grounding"
     },
     {
+      "name": "caption_grounding: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Language-to-Moment Grounding",
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "query features -> candidate index -> cosine ranker",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "ranked matching moments",
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "text-like query and candidate windows",
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Language Grounding",
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Retrieve the matching time window for an annotation-derived text query.",
       "raw_hits": []
     },
     {
       "observed": "cross_modal_retrieval"
     },
     {
+      "name": "cross_modal_retrieval: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Multimodal Representation Retrieval",
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "modality split -> projection -> nearest-neighbor ranker",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "ranked visual windows",
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "motion/IMU/pose query; depth/video candidates",
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Cross-Modal Retrieval",
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Use motion, IMU, and camera-pose signals to retrieve the matching depth/video window.",
       "raw_hits": []
     },
     {
       "observed": "modality_reconstruction"
     },
     {
+      "name": "modality_reconstruction: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Modality Feature Reconstruction",
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "source-target split -> scaler -> regression head",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "reconstructed depth/video vector",
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "motion, IMU, and camera/pose features",
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Cross-Modal Reconstruction",
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Predict compressed depth/video feature vectors from motion, IMU, and camera-pose features.",
       "raw_hits": []
     },
     {
       "observed": "temporal_order"
     },
     {
+      "name": "temporal_order: public_field_research_name_is_human_readable",
       "status": "pass",
       "value": "Temporal Order Verification",
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "pair builder -> feature combiner -> binary classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "correct or reversed",
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "two adjacent windows plus difference vector",
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Temporal Order Verification",
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Tell whether two neighboring windows are in chronological order or reversed.",
       "raw_hits": []
     },
     {
       "observed": "misalignment_detection"
     },
     {
+      "name": "misalignment_detection: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Cross-Modal Misalignment Detection",
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "aligned/shifted pairs -> feature combiner -> binary classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "aligned or shifted",
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "motion-side and visual/depth-side feature groups",
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Multimodal Synchronization Detection",
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Detect whether motion and visual/depth streams have been artificially shifted out of sync.",
       "raw_hits": []
     },
     {

docs/data/website_integrity.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-13T21:56:42+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
@@ -74,8 +74,8 @@
       "name": "project_overview_precedes_progress_ledger",
       "status": "pass",
       "reason": "The project overview should appear before the deeper progress ledger.",
-      "overview_index": 67412,
-      "evidence_index": 93059
     },
     {
       "name": "project_status_links_json",
@@ -153,9 +153,9 @@
       "name": "evaluation_protocol_between_overview_and_progress",
       "status": "pass",
       "reason": "The evaluation protocol should appear before the deeper evidence ledger.",
-      "overview_index": 67412,
-      "protocol_index": 89241,
-      "evidence_index": 93059
     },
     {
       "name": "evaluation_protocol_links_json",
@@ -167,7 +167,7 @@
       "name": "visual_figures_link_task_suite_image",
       "status": "pass",
       "reason": "The website should expose the main task-suite figure.",
-      "marker_count": 3
     },
     {
       "name": "suite_task_map_precedes_modality_atlas",
@@ -253,7 +253,7 @@
     },
     {
       "path": "data/artifact_index.json",
-      "bytes": 88913,
       "top_level_type": "dict"
     },
     {
@@ -293,7 +293,7 @@
     },
     {
       "path": "data/mirror_parity.json",
-      "bytes": 548190,
       "top_level_type": "dict"
     },
     {

 {
   "status": "pass",
+  "generated_at_utc": "2026-06-14T05:39:07+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
       "name": "project_overview_precedes_progress_ledger",
       "status": "pass",
       "reason": "The project overview should appear before the deeper progress ledger.",
+      "overview_index": 70501,
+      "evidence_index": 96148
     },
     {
       "name": "project_status_links_json",
       "name": "evaluation_protocol_between_overview_and_progress",
       "status": "pass",
       "reason": "The evaluation protocol should appear before the deeper evidence ledger.",
+      "overview_index": 70501,
+      "protocol_index": 92330,
+      "evidence_index": 96148
     },
     {
       "name": "evaluation_protocol_links_json",
       "name": "visual_figures_link_task_suite_image",
       "status": "pass",
       "reason": "The website should expose the main task-suite figure.",
+      "marker_count": 5
     },
     {
       "name": "suite_task_map_precedes_modality_atlas",
     },
     {
       "path": "data/artifact_index.json",
+      "bytes": 89995,
       "top_level_type": "dict"
     },
     {
     },
     {
       "path": "data/mirror_parity.json",
+      "bytes": 550970,
       "top_level_type": "dict"
     },
     {

metrics/artifact_index.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "title": "Ropedia Xperience-10M Task Suite Artifact Index",
-  "generated_at_utc": "2026-06-13T21:57:03+00:00",
   "status": "pass",
   "artifact_count": 164,
   "missing": [],
@@ -340,8 +340,8 @@
       "surface": "repo_hf",
       "shows": "Runs the owner-side Qwen3-Omni v6 one-sample reproduction smoke from a private staged model, adapter, JSONL, and exported media cache.",
       "exists": true,
-      "bytes": 2514,
-      "sha256": "65c692efa70e4440041bb4c1b7da2d92eded6b2925a22889caa1a18621e59247"
     },
     {
       "id": "qwen3_video_feature_compat_patch",
@@ -462,7 +462,7 @@
       "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
       "exists": true,
       "bytes": 4432,
-      "sha256": "b7f30209e242dd07a0a5de5154a0c8caf3d8988995591da2bd35ba5bce0aa4b8"
     },
     {
       "id": "source_alignment_validator",
@@ -841,7 +841,7 @@
       "shows": "Defines public reproduction commands, expected outputs, and non-reproducible scale-up boundaries.",
       "exists": true,
       "bytes": 9016,
-      "sha256": "765cd4e45e0844534839cc9bcfe473613fa76c2aa073c74ccb08ac15a51da197"
     },
     {
       "id": "reproducibility_matrix",
@@ -898,7 +898,7 @@
       "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": 548190,
       "hash_policy": "existence_and_size_only"
     },
     {

 {
   "title": "Ropedia Xperience-10M Task Suite Artifact Index",
+  "generated_at_utc": "2026-06-14T05:39:44+00:00",
   "status": "pass",
   "artifact_count": 164,
   "missing": [],
       "surface": "repo_hf",
       "shows": "Runs the owner-side Qwen3-Omni v6 one-sample reproduction smoke from a private staged model, adapter, JSONL, and exported media cache.",
       "exists": true,
+      "bytes": 4082,
+      "sha256": "23cdd97be6cc7f516d231f65646215ff7447f47243040920b1840c7e76c09ff1"
     },
     {
       "id": "qwen3_video_feature_compat_patch",
       "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
       "exists": true,
       "bytes": 4432,
+      "sha256": "24076a6db867af49f9b82d24b68816a1d2bbb4b31f7031aa89699326cb33539b"
     },
     {
       "id": "source_alignment_validator",
       "shows": "Defines public reproduction commands, expected outputs, and non-reproducible scale-up boundaries.",
       "exists": true,
       "bytes": 9016,
+      "sha256": "c1b9c7bd3fdd7446f41b1c4247727ce135697bfc3539b82cabd0d0c09fe7307f"
     },
     {
       "id": "reproducibility_matrix",
       "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": 550970,
       "hash_policy": "existence_and_size_only"
     },
     {

metrics/mirror_parity.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-13T22:21:20+00:00",
   "hf_root": "hf_publish",
   "summary": {
     "group_count": 369,
@@ -139,44 +139,44 @@
         "path": "repo:docs/data/artifact_index.json",
         "exists": true,
         "bytes": 89995,
-        "sha256": "ea0d373af376bad71330615ec537528343dd59bb07058fcb0e6e35e3d94ead9d"
       },
       "mirrors": {
         "hf_space": {
           "path": "hf_space:data/artifact_index.json",
           "exists": true,
           "bytes": 89995,
-          "sha256": "ea0d373af376bad71330615ec537528343dd59bb07058fcb0e6e35e3d94ead9d"
         },
         "hf_artifacts_data": {
           "path": "hf_artifacts:data/artifact_index.json",
           "exists": true,
           "bytes": 89995,
-          "sha256": "ea0d373af376bad71330615ec537528343dd59bb07058fcb0e6e35e3d94ead9d"
         },
         "hf_artifacts": {
           "path": "hf_artifacts:docs/data/artifact_index.json",
           "exists": true,
           "bytes": 89995,
-          "sha256": "ea0d373af376bad71330615ec537528343dd59bb07058fcb0e6e35e3d94ead9d"
         },
         "hf_model_data": {
           "path": "hf_model:data/artifact_index.json",
           "exists": true,
           "bytes": 89995,
-          "sha256": "ea0d373af376bad71330615ec537528343dd59bb07058fcb0e6e35e3d94ead9d"
         },
         "hf_model_docs_data": {
           "path": "hf_model:docs/data/artifact_index.json",
           "exists": true,
           "bytes": 89995,
-          "sha256": "ea0d373af376bad71330615ec537528343dd59bb07058fcb0e6e35e3d94ead9d"
         },
         "hf_model": {
           "path": "hf_model:metrics/artifact_index.json",
           "exists": true,
           "bytes": 89995,
-          "sha256": "ea0d373af376bad71330615ec537528343dd59bb07058fcb0e6e35e3d94ead9d"
         }
       },
       "failures": []
@@ -825,44 +825,44 @@
         "path": "repo:docs/data/publication_audit.json",
         "exists": true,
         "bytes": 7591,
-        "sha256": "df9cd69dbbef319d9d72c2d861d544ee8f6f30042e52046097259b2722e4632e"
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           "path": "hf_space:data/publication_audit.json",
           "exists": true,
           "bytes": 7591,
-          "sha256": "df9cd69dbbef319d9d72c2d861d544ee8f6f30042e52046097259b2722e4632e"
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         "hf_artifacts_data": {
           "path": "hf_artifacts:data/publication_audit.json",
           "exists": true,
           "bytes": 7591,
-          "sha256": "df9cd69dbbef319d9d72c2d861d544ee8f6f30042e52046097259b2722e4632e"
         },
         "hf_artifacts": {
           "path": "hf_artifacts:docs/data/publication_audit.json",
           "exists": true,
           "bytes": 7591,
-          "sha256": "df9cd69dbbef319d9d72c2d861d544ee8f6f30042e52046097259b2722e4632e"
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         "hf_model_data": {
           "path": "hf_model:data/publication_audit.json",
           "exists": true,
           "bytes": 7591,
-          "sha256": "df9cd69dbbef319d9d72c2d861d544ee8f6f30042e52046097259b2722e4632e"
         },
         "hf_model_docs_data": {
           "path": "hf_model:docs/data/publication_audit.json",
           "exists": true,
           "bytes": 7591,
-          "sha256": "df9cd69dbbef319d9d72c2d861d544ee8f6f30042e52046097259b2722e4632e"
         },
         "hf_model": {
           "path": "hf_model:metrics/publication_audit.json",
           "exists": true,
           "bytes": 7591,
-          "sha256": "df9cd69dbbef319d9d72c2d861d544ee8f6f30042e52046097259b2722e4632e"
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       "failures": []
@@ -874,44 +874,44 @@
         "path": "repo:docs/data/public_surface_qa.json",
         "exists": true,
         "bytes": 5640,
-        "sha256": "3d5f12f1f2e883054494ffce168aa00298812547ada8dec7794178397c25660b"
       },
       "mirrors": {
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           "path": "hf_space:data/public_surface_qa.json",
           "exists": true,
           "bytes": 5640,
-          "sha256": "3d5f12f1f2e883054494ffce168aa00298812547ada8dec7794178397c25660b"
         },
         "hf_artifacts_data": {
           "path": "hf_artifacts:data/public_surface_qa.json",
           "exists": true,
           "bytes": 5640,
-          "sha256": "3d5f12f1f2e883054494ffce168aa00298812547ada8dec7794178397c25660b"
         },
         "hf_artifacts": {
           "path": "hf_artifacts:docs/data/public_surface_qa.json",
           "exists": true,
           "bytes": 5640,
-          "sha256": "3d5f12f1f2e883054494ffce168aa00298812547ada8dec7794178397c25660b"
         },
         "hf_model_data": {
           "path": "hf_model:data/public_surface_qa.json",
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@@ -1,7 +1,7 @@
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 {
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@@ -1,6 +1,6 @@
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@@ -1,6 +1,6 @@
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     "dataset_manifest_num_episodes": 119,

 {
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@@ -1,6 +1,6 @@
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@@ -1,7 +1,7 @@
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 {
   "title": "Ropedia Xperience-10M Source Alignment Note",
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   "alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
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@@ -1,6 +1,6 @@
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@@ -64,15 +64,15 @@
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@@ -82,27 +82,27 @@
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@@ -184,15 +184,15 @@
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@@ -202,27 +202,27 @@
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@@ -304,15 +304,15 @@
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@@ -322,27 +322,27 @@
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     },
     {
-      "name": "transition_detection: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "boundary or steady",
       "raw_hits": []
     },
     {
-      "name": "transition_detection: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "action changes -> boundary labels -> binary classifier",
       "raw_hits": []
     },
     {
@@ -422,15 +422,15 @@
       "observed": "next_action"
     },
     {
-      "name": "next_action: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Next-Action Prediction",
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "current window at time t",
       "raw_hits": []
     },
     {
@@ -440,27 +440,27 @@
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Short-Horizon Intention Prediction",
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Forecast the near-future action from the current observations only.",
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "action at t+20 frames",
       "raw_hits": []
     },
     {
-      "name": "next_action: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "current features -> future label shift -> classifier",
       "raw_hits": []
     },
     {
@@ -540,15 +540,15 @@
       "observed": "hand_trajectory_forecast"
     },
     {
-      "name": "hand_trajectory_forecast: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Hand Trajectory Forecasting",
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "current multimodal window",
       "raw_hits": []
     },
     {
@@ -558,27 +558,27 @@
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "3D Hand Motion Forecasting",
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Predict the future 3D left/right hand path from the current multimodal state.",
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "future hand-joint trajectory",
       "raw_hits": []
     },
     {
-      "name": "hand_trajectory_forecast: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "current features -> future mocap target -> regression head",
       "raw_hits": []
     },
     {
@@ -658,15 +658,15 @@
       "observed": "contact_prediction"
     },
     {
-      "name": "contact_prediction: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Contact State Prediction",
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "non-contact, non-caption features",
       "raw_hits": []
     },
     {
@@ -676,27 +676,27 @@
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Human-Object Contact Prediction",
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Predict whether body or hand contact with the scene is occurring without leaking contact labels.",
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "contact or no contact",
       "raw_hits": []
     },
     {
-      "name": "contact_prediction: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "feature filter -> contact target -> binary classifier",
       "raw_hits": []
     },
     {
@@ -774,15 +774,15 @@
       "observed": "object_relevance"
     },
     {
-      "name": "object_relevance: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Object Relevance Prediction",
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "non-caption multimodal features",
       "raw_hits": []
     },
     {
@@ -792,27 +792,27 @@
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Object-Centric Interaction Recognition",
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Infer which objects are relevant to the current manipulation window from non-caption features.",
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "relevant object set",
       "raw_hits": []
     },
     {
-      "name": "object_relevance: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "object vocabulary -> multi-hot labels -> sigmoid heads",
       "raw_hits": []
     },
     {
@@ -892,15 +892,15 @@
       "observed": "caption_grounding"
     },
     {
-      "name": "caption_grounding: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Language Grounding",
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "text-like query and candidate windows",
       "raw_hits": []
     },
     {
@@ -910,27 +910,27 @@
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Language-to-Moment Grounding",
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Retrieve the matching time window for an annotation-derived text query.",
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "ranked matching moments",
       "raw_hits": []
     },
     {
-      "name": "caption_grounding: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "query features -> candidate index -> cosine ranker",
       "raw_hits": []
     },
     {
@@ -1008,15 +1008,15 @@
       "observed": "cross_modal_retrieval"
     },
     {
-      "name": "cross_modal_retrieval: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Cross-Modal Retrieval",
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "motion/IMU/pose query; depth/video candidates",
       "raw_hits": []
     },
     {
@@ -1026,27 +1026,27 @@
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Multimodal Representation Retrieval",
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Use motion, IMU, and camera-pose signals to retrieve the matching depth/video window.",
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "ranked visual windows",
       "raw_hits": []
     },
     {
-      "name": "cross_modal_retrieval: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "modality split -> projection -> nearest-neighbor ranker",
       "raw_hits": []
     },
     {
@@ -1126,15 +1126,15 @@
       "observed": "modality_reconstruction"
     },
     {
-      "name": "modality_reconstruction: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Cross-Modal Reconstruction",
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "motion, IMU, and camera/pose features",
       "raw_hits": []
     },
     {
@@ -1144,27 +1144,27 @@
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Modality Feature Reconstruction",
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Predict compressed depth/video feature vectors from motion, IMU, and camera-pose features.",
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "reconstructed depth/video vector",
       "raw_hits": []
     },
     {
-      "name": "modality_reconstruction: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "source-target split -> scaler -> regression head",
       "raw_hits": []
     },
     {
@@ -1244,15 +1244,15 @@
       "observed": "temporal_order"
     },
     {
-      "name": "temporal_order: public_field_display_name_is_human_readable",
       "status": "pass",
       "value": "Temporal Order Verification",
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "two adjacent windows plus difference vector",
       "raw_hits": []
     },
     {
@@ -1262,27 +1262,27 @@
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Temporal Order Verification",
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Tell whether two neighboring windows are in chronological order or reversed.",
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "correct or reversed",
       "raw_hits": []
     },
     {
-      "name": "temporal_order: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "pair builder -> feature combiner -> binary classifier",
       "raw_hits": []
     },
     {
@@ -1360,15 +1360,15 @@
       "observed": "misalignment_detection"
     },
     {
-      "name": "misalignment_detection: public_field_display_name_is_human_readable",
       "status": "pass",
-      "value": "Multimodal Synchronization Detection",
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_input_short_is_human_readable",
       "status": "pass",
-      "value": "motion-side and visual/depth-side feature groups",
       "raw_hits": []
     },
     {
@@ -1378,27 +1378,27 @@
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_research_name_is_human_readable",
       "status": "pass",
-      "value": "Cross-Modal Misalignment Detection",
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_card_blurb_is_human_readable",
       "status": "pass",
-      "value": "Detect whether motion and visual/depth streams have been artificially shifted out of sync.",
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_output_short_is_human_readable",
       "status": "pass",
-      "value": "aligned or shifted",
       "raw_hits": []
     },
     {
-      "name": "misalignment_detection: public_field_process_short_is_human_readable",
       "status": "pass",
-      "value": "aligned/shifted pairs -> feature combiner -> binary classifier",
       "raw_hits": []
     },
     {

 {
   "status": "pass",
+  "generated_at_utc": "2026-06-14T05:33:57+00:00",
   "summary": {
     "task_count": 12,
     "expected_task_count": 12,
       "observed": "timeline_action"
     },
     {
+      "name": "timeline_action: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Egocentric Action Recognition",
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "window features -> action label builder -> classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "current action class",
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "20-frame multimodal window",
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Action Recognition",
       "raw_hits": []
     },
     {
+      "name": "timeline_action: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Recognize the current manipulation action from synchronized visual, motion, inertial, pose, and annotation context.",
       "raw_hits": []
     },
     {
       "observed": "timeline_subtask"
     },
     {
+      "name": "timeline_subtask: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Temporal Subtask Recognition",
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "window features -> subtask label builder -> classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "current procedure step",
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "20-frame multimodal window",
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Procedure Step Recognition",
       "raw_hits": []
     },
     {
+      "name": "timeline_subtask: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Recognize the broader activity stage so fine actions become a readable procedure timeline.",
       "raw_hits": []
     },
     {
       "observed": "transition_detection"
     },
     {
+      "name": "transition_detection: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Temporal Action Segmentation",
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "action changes -> boundary labels -> binary classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "boundary or steady",
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "current window with boundary target",
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Action Boundary Detection",
       "raw_hits": []
     },
     {
+      "name": "transition_detection: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Detect the local moment where the episode changes from one action segment to the next.",
       "raw_hits": []
     },
     {
       "observed": "next_action"
     },
     {
+      "name": "next_action: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Short-Horizon Intention Prediction",
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "current features -> future label shift -> classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "action at t+20 frames",
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "current window at time t",
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Next-Action Prediction",
       "raw_hits": []
     },
     {
+      "name": "next_action: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Forecast the near-future action from the current observations only.",
       "raw_hits": []
     },
     {
       "observed": "hand_trajectory_forecast"
     },
     {
+      "name": "hand_trajectory_forecast: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "3D Hand Motion Forecasting",
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "current features -> future mocap target -> regression head",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "future hand-joint trajectory",
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "current multimodal window",
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Hand Trajectory Forecasting",
       "raw_hits": []
     },
     {
+      "name": "hand_trajectory_forecast: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Predict the future 3D left/right hand path from the current multimodal state.",
       "raw_hits": []
     },
     {
       "observed": "contact_prediction"
     },
     {
+      "name": "contact_prediction: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Human-Object Contact Prediction",
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "feature filter -> contact target -> binary classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "contact or no contact",
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "non-contact, non-caption features",
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Contact State Prediction",
       "raw_hits": []
     },
     {
+      "name": "contact_prediction: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Predict whether body or hand contact with the scene is occurring without leaking contact labels.",
       "raw_hits": []
     },
     {
       "observed": "object_relevance"
     },
     {
+      "name": "object_relevance: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Object-Centric Interaction Recognition",
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "object vocabulary -> multi-hot labels -> sigmoid heads",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "relevant object set",
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "non-caption multimodal features",
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Object Relevance Prediction",
       "raw_hits": []
     },
     {
+      "name": "object_relevance: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Infer which objects are relevant to the current manipulation window from non-caption features.",
       "raw_hits": []
     },
     {
       "observed": "caption_grounding"
     },
     {
+      "name": "caption_grounding: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Language-to-Moment Grounding",
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "query features -> candidate index -> cosine ranker",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "ranked matching moments",
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "text-like query and candidate windows",
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Language Grounding",
       "raw_hits": []
     },
     {
+      "name": "caption_grounding: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Retrieve the matching time window for an annotation-derived text query.",
       "raw_hits": []
     },
     {
       "observed": "cross_modal_retrieval"
     },
     {
+      "name": "cross_modal_retrieval: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Multimodal Representation Retrieval",
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "modality split -> projection -> nearest-neighbor ranker",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "ranked visual windows",
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "motion/IMU/pose query; depth/video candidates",
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Cross-Modal Retrieval",
       "raw_hits": []
     },
     {
+      "name": "cross_modal_retrieval: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Use motion, IMU, and camera-pose signals to retrieve the matching depth/video window.",
       "raw_hits": []
     },
     {
       "observed": "modality_reconstruction"
     },
     {
+      "name": "modality_reconstruction: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Modality Feature Reconstruction",
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "source-target split -> scaler -> regression head",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "reconstructed depth/video vector",
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "motion, IMU, and camera/pose features",
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Cross-Modal Reconstruction",
       "raw_hits": []
     },
     {
+      "name": "modality_reconstruction: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Predict compressed depth/video feature vectors from motion, IMU, and camera-pose features.",
       "raw_hits": []
     },
     {
       "observed": "temporal_order"
     },
     {
+      "name": "temporal_order: public_field_research_name_is_human_readable",
       "status": "pass",
       "value": "Temporal Order Verification",
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "pair builder -> feature combiner -> binary classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "correct or reversed",
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "two adjacent windows plus difference vector",
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Temporal Order Verification",
       "raw_hits": []
     },
     {
+      "name": "temporal_order: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Tell whether two neighboring windows are in chronological order or reversed.",
       "raw_hits": []
     },
     {
       "observed": "misalignment_detection"
     },
     {
+      "name": "misalignment_detection: public_field_research_name_is_human_readable",
       "status": "pass",
+      "value": "Cross-Modal Misalignment Detection",
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_process_short_is_human_readable",
       "status": "pass",
+      "value": "aligned/shifted pairs -> feature combiner -> binary classifier",
       "raw_hits": []
     },
     {
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_output_short_is_human_readable",
       "status": "pass",
+      "value": "aligned or shifted",
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_input_short_is_human_readable",
       "status": "pass",
+      "value": "motion-side and visual/depth-side feature groups",
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_display_name_is_human_readable",
       "status": "pass",
+      "value": "Multimodal Synchronization Detection",
       "raw_hits": []
     },
     {
+      "name": "misalignment_detection: public_field_card_blurb_is_human_readable",
       "status": "pass",
+      "value": "Detect whether motion and visual/depth streams have been artificially shifted out of sync.",
       "raw_hits": []
     },
     {

metrics/website_integrity.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-13T21:56:42+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
@@ -74,8 +74,8 @@
       "name": "project_overview_precedes_progress_ledger",
       "status": "pass",
       "reason": "The project overview should appear before the deeper progress ledger.",
-      "overview_index": 67412,
-      "evidence_index": 93059
     },
     {
       "name": "project_status_links_json",
@@ -153,9 +153,9 @@
       "name": "evaluation_protocol_between_overview_and_progress",
       "status": "pass",
       "reason": "The evaluation protocol should appear before the deeper evidence ledger.",
-      "overview_index": 67412,
-      "protocol_index": 89241,
-      "evidence_index": 93059
     },
     {
       "name": "evaluation_protocol_links_json",
@@ -167,7 +167,7 @@
       "name": "visual_figures_link_task_suite_image",
       "status": "pass",
       "reason": "The website should expose the main task-suite figure.",
-      "marker_count": 3
     },
     {
       "name": "suite_task_map_precedes_modality_atlas",
@@ -253,7 +253,7 @@
     },
     {
       "path": "data/artifact_index.json",
-      "bytes": 88913,
       "top_level_type": "dict"
     },
     {
@@ -293,7 +293,7 @@
     },
     {
       "path": "data/mirror_parity.json",
-      "bytes": 548190,
       "top_level_type": "dict"
     },
     {

 {
   "status": "pass",
+  "generated_at_utc": "2026-06-14T05:39:07+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
       "name": "project_overview_precedes_progress_ledger",
       "status": "pass",
       "reason": "The project overview should appear before the deeper progress ledger.",
+      "overview_index": 70501,
+      "evidence_index": 96148
     },
     {
       "name": "project_status_links_json",
       "name": "evaluation_protocol_between_overview_and_progress",
       "status": "pass",
       "reason": "The evaluation protocol should appear before the deeper evidence ledger.",
+      "overview_index": 70501,
+      "protocol_index": 92330,
+      "evidence_index": 96148
     },
     {
       "name": "evaluation_protocol_links_json",
       "name": "visual_figures_link_task_suite_image",
       "status": "pass",
       "reason": "The website should expose the main task-suite figure.",
+      "marker_count": 5
     },
     {
       "name": "suite_task_map_precedes_modality_atlas",
     },
     {
       "path": "data/artifact_index.json",
+      "bytes": 89995,
       "top_level_type": "dict"
     },
     {
     },
     {
       "path": "data/mirror_parity.json",
+      "bytes": 550970,
       "top_level_type": "dict"
     },
     {

scripts/build_single_episode_explorer.py CHANGED Viewed

@@ -16,7 +16,7 @@ from pathlib import Path
 import numpy as np
-from task_display import task_display_name
 TASK_DISPLAY = {
@@ -27,6 +27,7 @@ TASK_DISPLAY = {
     "contact_prediction": task_display_name("contact_prediction"),
     "object_relevance": task_display_name("object_relevance"),
 }
 BLOCK_DISPLAY = {
@@ -66,7 +67,7 @@ def read_json(path: Path):
 def write_json(path: Path, data: dict) -> None:
     path.parent.mkdir(parents=True, exist_ok=True)
-    path.write_text(json.dumps(data, indent=2, ensure_ascii=False), encoding="utf-8")
 def block_modality(name: str) -> str:
@@ -157,8 +158,8 @@ def build_data(args: argparse.Namespace) -> dict:
     ablation_rows = read_csv(diagnostics_dir / "modality_ablation/ablation_metrics.csv")
     for row in ablation_rows:
         task = row.get("task")
-        if task in TASK_DISPLAY:
-            row["task_display_name"] = TASK_DISPLAY[task]
     alignment_rows = read_csv(diagnostics_dir / "alignment_stress/alignment_shift_metrics.csv")
     timeline_rows = read_csv(diagnostics_dir / "timeline_overlay/timeline_overlay.csv")
     predictions = load_predictions(suite_dir)
@@ -259,7 +260,7 @@ def build_data(args: argparse.Namespace) -> dict:
             },
         },
         "tasks": TASK_DISPLAY,
-        "task_display_names": TASK_DISPLAY,
         "feature_blocks": block_meta,
         "segments": build_action_segments(windows),
         "windows": explorer_windows,
@@ -286,7 +287,7 @@ HTML_TEMPLATE = """<!doctype html>
   <style>
     :root { color-scheme: dark; --page:#020502; --panel:#071207; --surface:#0b1709; --ink:#f4f8ef; --muted:#a7b5a3; --line:rgba(204,255,160,.24); --soft:rgba(204,255,160,.14); --green:#ccffa0; --cyan:#7ae5c3; --blue:#9bdfff; --red:#ff8f7a; --amber:#d8f4a5; --card:rgba(5,10,6,.84); --pill:rgba(255,255,255,.05); --font-ui:"Inter Tight",ui-sans-serif,system-ui,-apple-system,BlinkMacSystemFont,"Segoe UI",sans-serif; --font-copy:"Inter Tight",ui-sans-serif,system-ui,-apple-system,BlinkMacSystemFont,"Segoe UI",sans-serif; --font-btn:"Space Grotesk",ui-sans-serif,system-ui,-apple-system,BlinkMacSystemFont,"Segoe UI",sans-serif; --max:1400px; }
     * { box-sizing:border-box; }
-    body { margin:0; background: radial-gradient(circle at 80% 12%, rgba(204,255,160,.13), transparent 28%), radial-gradient(circle, rgba(204,255,160,.10) 1px, transparent 1.4px), var(--page); background-size:auto,22px 22px,auto; color:var(--ink); font-family:var(--font-copy); line-height:1.5; font-synthesis-weight:none; }
     a { color:inherit; }
     .wrap { width:min(var(--max), calc(100% - 42px)); margin:0 auto; }
     header { position:sticky; top:0; z-index:10; background:rgba(2,5,2,.92); backdrop-filter:blur(16px); border-bottom:1px solid var(--soft); }
@@ -296,7 +297,7 @@ HTML_TEMPLATE = """<!doctype html>
     .nav-links { display:flex; gap:10px; color:#c9d5c5; font-family:var(--font-btn); font-size:14px; }
     .nav-links a { min-height:36px; display:inline-flex; align-items:center; justify-content:center; padding:0 14px; border:1px solid transparent; border-radius:999px; background:var(--pill); text-decoration:none; }
     .nav-links a:hover { border-color:var(--green); color:var(--green); background:rgba(255,255,255,.08); }
-    .hero { padding:54px 0 30px; border-bottom:1px solid var(--soft); background:#05060b; }
     h1 { max-width:900px; margin:0; font-family:var(--font-ui); font-size:clamp(42px, 6vw, 76px); line-height:.98; letter-spacing:0; }
     .hero p { max-width:820px; margin:22px 0 0; color:#c7d1c3; font-size:18px; line-height:1.62; }
     .stats { display:grid; grid-template-columns:repeat(4,minmax(0,1fr)); gap:10px; margin-top:28px; max-width:900px; }

 import numpy as np
+from task_display import TASK_DISPLAY_NAMES, task_display_name
 TASK_DISPLAY = {
     "contact_prediction": task_display_name("contact_prediction"),
     "object_relevance": task_display_name("object_relevance"),
 }
+TASK_DISPLAY_ALL = dict(TASK_DISPLAY_NAMES)
 BLOCK_DISPLAY = {
 def write_json(path: Path, data: dict) -> None:
     path.parent.mkdir(parents=True, exist_ok=True)
+    path.write_text(json.dumps(data, indent=2, ensure_ascii=False) + "\n", encoding="utf-8")
 def block_modality(name: str) -> str:
     ablation_rows = read_csv(diagnostics_dir / "modality_ablation/ablation_metrics.csv")
     for row in ablation_rows:
         task = row.get("task")
+        if task in TASK_DISPLAY_ALL:
+            row["task_display_name"] = TASK_DISPLAY_ALL[task]
     alignment_rows = read_csv(diagnostics_dir / "alignment_stress/alignment_shift_metrics.csv")
     timeline_rows = read_csv(diagnostics_dir / "timeline_overlay/timeline_overlay.csv")
     predictions = load_predictions(suite_dir)
             },
         },
         "tasks": TASK_DISPLAY,
+        "task_display_names": TASK_DISPLAY_ALL,
         "feature_blocks": block_meta,
         "segments": build_action_segments(windows),
         "windows": explorer_windows,
   <style>
     :root { color-scheme: dark; --page:#020502; --panel:#071207; --surface:#0b1709; --ink:#f4f8ef; --muted:#a7b5a3; --line:rgba(204,255,160,.24); --soft:rgba(204,255,160,.14); --green:#ccffa0; --cyan:#7ae5c3; --blue:#9bdfff; --red:#ff8f7a; --amber:#d8f4a5; --card:rgba(5,10,6,.84); --pill:rgba(255,255,255,.05); --font-ui:"Inter Tight",ui-sans-serif,system-ui,-apple-system,BlinkMacSystemFont,"Segoe UI",sans-serif; --font-copy:"Inter Tight",ui-sans-serif,system-ui,-apple-system,BlinkMacSystemFont,"Segoe UI",sans-serif; --font-btn:"Space Grotesk",ui-sans-serif,system-ui,-apple-system,BlinkMacSystemFont,"Segoe UI",sans-serif; --max:1400px; }
     * { box-sizing:border-box; }
+    body { margin:0; background:var(--page); color:var(--ink); font-family:var(--font-copy); line-height:1.5; font-synthesis-weight:none; }
     a { color:inherit; }
     .wrap { width:min(var(--max), calc(100% - 42px)); margin:0 auto; }
     header { position:sticky; top:0; z-index:10; background:rgba(2,5,2,.92); backdrop-filter:blur(16px); border-bottom:1px solid var(--soft); }
     .nav-links { display:flex; gap:10px; color:#c9d5c5; font-family:var(--font-btn); font-size:14px; }
     .nav-links a { min-height:36px; display:inline-flex; align-items:center; justify-content:center; padding:0 14px; border:1px solid transparent; border-radius:999px; background:var(--pill); text-decoration:none; }
     .nav-links a:hover { border-color:var(--green); color:var(--green); background:rgba(255,255,255,.08); }
+    .hero { padding:78px 0 38px; border-bottom:1px solid var(--soft); background:linear-gradient(90deg, rgba(2,5,2,.95) 0%, rgba(2,5,2,.82) 55%, rgba(2,5,2,.70) 100%), linear-gradient(180deg, rgba(2,5,2,.08), rgba(5,6,11,.96)), url("assets/modalities/video.jpg") center right / cover no-repeat; }
     h1 { max-width:900px; margin:0; font-family:var(--font-ui); font-size:clamp(42px, 6vw, 76px); line-height:.98; letter-spacing:0; }
     .hero p { max-width:820px; margin:22px 0 0; color:#c7d1c3; font-size:18px; line-height:1.62; }
     .stats { display:grid; grid-template-columns:repeat(4,minmax(0,1fr)); gap:10px; margin-top:28px; max-width:900px; }