Add files using upload-large-folder tool

data/artifact_index.json

@@ -1,6 +1,6 @@
 {
   "title": "Ropedia Xperience-10M Task Suite Artifact Index",
-  "generated_at_utc": "2026-06-21T14:40:34+00:00",
+  "generated_at_utc": "2026-06-21T15:19:00+00:00",
   "status": "pass",
   "artifact_count": 228,
   "missing": [],
@@ -59,8 +59,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable first-reader project brief for the website and Hugging Face mirrors.",
       "exists": true,
-      "bytes": 4019,
-      "sha256": "9521556a750941a0f9ee8e9541903acbb0fbec2501fd05ed4e7a017fc18cf794"
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     },
     {
       "id": "project_status",
@@ -70,8 +70,8 @@
       "surface": "repo_hf",
       "shows": "Gives a compact current-state table for first-pass readers.",
       "exists": true,
-      "bytes": 15993,
-      "sha256": "96bf5d894ace804aea2f3889a4d99a802a5e015405e7eed573eb3a98882ce968"
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+      "sha256": "5ad142b601ad982ce59620bd7fa50446c8837050b0331b2be4a357280b295c21"
     },
     {
       "id": "project_status_json",
@@ -81,8 +81,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable copy of the current project status for website and HF mirrors.",
       "exists": true,
-      "bytes": 23255,
-      "sha256": "874f1133ee75f060735f0c9e763cf81463f304432f1dbca3ebc9837225c0259d"
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+      "sha256": "406c48ec858b5f288c7ebef6eefc0ed94dc8bad11bf9221f435b9c8aca547ea3"
     },
     {
       "id": "glossary",
@@ -576,8 +576,8 @@
       "surface": "website_hf",
       "shows": "Gives a short project path with scope status and public surfaces.",
       "exists": true,
-      "bytes": 10009,
-      "sha256": "e0f8bd65cd15b0fe68c8079045b4c72552daaf644c35b8a7a68426250a4aa441"
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     },
     {
       "id": "artifact_guide",
@@ -587,8 +587,8 @@
       "surface": "repo_hf",
       "shows": "Gives the human-readable map from project scope to data, tasks, platform mirrors, and scale-up status.",
       "exists": true,
-      "bytes": 20571,
-      "sha256": "217e3eb2cf82999f75ce6e132f567fa1ed08d319bf7a44f77b7150a45fae5274"
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     },
     {
       "id": "official_dataset_card_alignment",
@@ -632,7 +632,7 @@
       "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
       "exists": true,
       "bytes": 4432,
-      "sha256": "3def3dc923162ad0d2802acdca8a689a4e9ad1408f36edae8f77f49c4507cef1"
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     },
     {
       "id": "source_alignment_validator",
@@ -686,8 +686,8 @@
       "surface": "repo_hf",
       "shows": "Defines the window unit, chronological split, task metrics, leakage controls, and current limitations.",
       "exists": true,
-      "bytes": 9156,
-      "sha256": "cfc23b3115ebce2b41a349b8a2cd6989aaf2294790c79e2b17545ebede2b2df0"
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     },
     {
       "id": "evaluation_protocol_json",
@@ -697,8 +697,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable protocol generated from committed task metrics for website and HF mirrors.",
       "exists": true,
-      "bytes": 24007,
-      "sha256": "dde490d175f0d6828f5973f1b24e696a3d1b3b09d65a59cb9c1dde5c38845b66"
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+      "sha256": "d8f61b646a2f3f1e0af901dbdaff310ebfeea90622c93a34b9e35f34be98b896"
     },
     {
       "id": "evaluation_protocol_builder",
@@ -708,8 +708,8 @@
       "surface": "repo_hf",
       "shows": "Regenerates the protocol from committed summary metrics and task artifacts.",
       "exists": true,
-      "bytes": 19931,
-      "sha256": "080f894b50c609e3a467c8c513dfe441f90ba0dad3586dd1cb88de6e58eedb3b"
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     },
     {
       "id": "task_suite_20",
@@ -719,8 +719,8 @@
       "surface": "repo_hf",
       "shows": "Reader-facing table for the single unified public-sample task suite under the same window, split, feature, and baseline contract.",
       "exists": true,
-      "bytes": 5196,
-      "sha256": "473891503dcd1251a2cc9a16e6642ce16fbca9d264a734d2397c2afc60977195"
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+      "sha256": "076a68734f20e2660d1eddba460672c1246951b893494396f1281d6423f3627a"
     },
     {
       "id": "task_suite_20_json",
@@ -730,8 +730,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable unified 20-task index for the website, Hugging Face mirrors, and live verification.",
       "exists": true,
-      "bytes": 34597,
-      "sha256": "2029f7f9744001861ac00acabdb578fe97d3b39a1c16a7c2d19c56347ded22d7"
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+      "sha256": "75145285cf71bc3bb9a10377a1921b60e85c4546dc8b858102b3c26e94c11a01"
     },
     {
       "id": "task_suite_20_builder",
@@ -741,8 +741,8 @@
       "surface": "repo_hf",
       "shows": "Regenerates the unified 20-task JSON and Markdown from the public-sample metrics plus the historical provenance result bundle.",
       "exists": true,
-      "bytes": 12213,
-      "sha256": "1421593f05e345799007bbcdf138f81dfdb7c511ec1e31b56d00e2cdaed3d7de"
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+      "sha256": "157265b5c025f279ce1eb56c52dd720ce0969b8426d5887030bfa179a3b565e0"
     },
     {
       "id": "unified_task_model_radar_json",
@@ -1005,8 +1005,8 @@
       "surface": "repo_hf",
       "shows": "Summarizes the main research lessons from committed metrics and identifies which experiments need held-out episodes.",
       "exists": true,
-      "bytes": 5172,
-      "sha256": "39978c1e30b6aa76c5fd2684e9a1111ec2e813423feaff6053084b0335968db8"
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+      "sha256": "385d1b77b41c632925bbd27878c334839303462d03a3b9d358326951b1088da8"
     },
     {
       "id": "research_takeaways_json",
@@ -1016,8 +1016,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable result interpretation for the website, HF cards, and mirror checks.",
       "exists": true,
-      "bytes": 7162,
-      "sha256": "9899c5cb6b92bcfe5e64f98503af5b7d0759ad1a9c5098dbfe4146f54ee26656"
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+      "sha256": "f1ddead60f986e3036206bc3c70d4bdda422a8be4761b285eb89c9c49d9832b6"
     },
     {
       "id": "research_takeaways_builder",
@@ -1027,8 +1027,8 @@
       "surface": "repo_hf",
       "shows": "Regenerates the research takeaways from committed summary metrics and task result artifacts.",
       "exists": true,
-      "bytes": 13496,
-      "sha256": "c35995607dc16fa2a318c626b84323eb47b61a373a492c22cf9fdac851b4d9b5"
+      "bytes": 13499,
+      "sha256": "fc749125f9be87ee0db5b66918342da5c0378d6c97fb1acabe9688f920554c39"
     },
     {
       "id": "audio_ablation_script",
@@ -1036,7 +1036,7 @@
       "path": "scripts/audio_ablation_and_raw_upgrade.py",
       "kind": "result_interpretation",
       "surface": "repo_hf",
-      "shows": "Measures audio contribution variants across the original task contracts.",
+      "shows": "Measures audio contribution variants across the walkthrough-backed task contracts.",
       "exists": true,
       "bytes": 43159,
       "sha256": "2444f2e52efb975be931b33d66b7180d53031e1d5e821719122160f92f4540aa"
@@ -1080,7 +1080,7 @@
       "path": "docs/assets/charts/audio_ablation_delta.svg",
       "kind": "visual_evidence",
       "surface": "website_hf",
-      "shows": "Bar chart of measured current-audio primary-metric deltas across the original tasks.",
+      "shows": "Bar chart of measured current-audio primary-metric deltas across the walkthrough-backed tasks.",
       "exists": true,
       "bytes": 4146,
       "sha256": "187dbabe01f9ff18841ff61a1e7fbf85bebdd188cc0f248bb5090d64528e7568"
@@ -1093,8 +1093,8 @@
       "surface": "repo_hf",
       "shows": "Catalogs public figures, charts, modality thumbnails, dimensions, hashes, roles, and source scripts.",
       "exists": true,
-      "bytes": 7011,
-      "sha256": "f6554cd980efa6c0b3b8feac5ff3e19c3e2e74ccf2d446ac4afb5ee5d65413f3"
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+      "sha256": "b7b507c35cd3cba2765586e9703a447c8025c89658c3daa390df67db4211d0fc"
     },
     {
       "id": "figure_index_json",
@@ -1104,8 +1104,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable visual asset index for website and Hugging Face mirrors.",
       "exists": true,
-      "bytes": 19469,
-      "sha256": "11a06ee64d28f81f3280eb99327d99b47dc58fb1521332434b9df11c97b9b4e8"
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+      "sha256": "4f225bf08f00fbe843999d6bd2b3d5f5d6c17f2ff67e1f6a85eee9094c6bb6a3"
     },
     {
       "id": "figure_index_builder",
@@ -1115,8 +1115,8 @@
       "surface": "repo_hf",
       "shows": "Regenerates visual-asset hashes, dimensions, and source-script provenance.",
       "exists": true,
-      "bytes": 16829,
-      "sha256": "14f1ed7f94630c8f70fbc14547071db251647f3d527cf760341b7a233883d069"
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+      "sha256": "3f91f7f13a3fb08ab57c2f0a6b320102e9d5ae19b102b71499edb5b8fd5a2cec"
     },
     {
       "id": "brand_assets_json",
@@ -1182,7 +1182,7 @@
       "shows": "Machine-readable release-check summary for validators, mirrors, and public project surfaces.",
       "exists": true,
       "bytes": 8640,
-      "sha256": "c8ce99ac63ab70e3696386671bf201f5605b6a88c8be8f288d44a122bad9025e"
+      "sha256": "6e54f6828b8fef97e963a9a56bccc91162b8a632f6897743095e32407fa0db98"
     },
     {
       "id": "public_surface_qa",
@@ -1226,7 +1226,7 @@
       "volatile": true,
       "shows": "Machine-readable report for SEO/social metadata, accessible tab semantics, public links, project links, and clear project presentation.",
       "exists": true,
-      "bytes": 7690,
+      "bytes": 7691,
       "hash_policy": "existence_and_size_only"
     },
     {
@@ -1307,7 +1307,7 @@
       "volatile": true,
       "shows": "Records the last live GitHub/HF URL verification after upload.",
       "exists": true,
-      "bytes": 189922,
+      "bytes": 189990,
       "hash_policy": "existence_and_size_only"
     },
     {
@@ -1340,8 +1340,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable reproduction steps with expected artifacts and public boundaries.",
       "exists": true,
-      "bytes": 6815,
-      "sha256": "ff44893cac56c229d6eb5d20d8cb261ea38e0358e6444615406affd692d8d98e"
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+      "sha256": "3f1e1615c6c0853d21bc14a8eab20af3757ecc443e72dab7744b3c0ec149fa87"
     },
     {
       "id": "artifact_index_builder",
@@ -1351,8 +1351,8 @@
       "surface": "repo_hf",
       "shows": "Generates the selective artifact catalog from local files.",
       "exists": true,
-      "bytes": 68232,
-      "sha256": "ee1b210688c1b722d6ca94d1c1706c1a510218c964298b91dd3e596fa19ed2a1"
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+      "sha256": "69b43ad5d3dc5a6893c4592fa47fff6a7a87691728ec2c61b121ec262d00bf2a"
     },
     {
       "id": "publication_audit",
@@ -1410,8 +1410,8 @@
       "surface": "website_hf",
       "shows": "Lists public URLs, upstream sources, and machine-readable project metadata.",
       "exists": true,
-      "bytes": 5774,
-      "sha256": "8da6063de9e0b888089aa62daac6d323057dd80247b8f38be5fbce0b370ef6ac"
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+      "sha256": "d972f30552dd346ec296f88d004c70bf2fb99e92e44ddc8d3a6dad5634f0336d"
     },
     {
       "id": "task_summary",
@@ -1474,7 +1474,7 @@
       "path": "results/episode_task_suite/neural_mlp",
       "kind": "result_directory",
       "surface": "repo_hf_model",
-      "shows": "Stores matching PyTorch MLP results for the original task contracts.",
+      "shows": "Stores matching PyTorch MLP results for the walkthrough-backed task contracts.",
       "exists": true,
       "file_count": 60,
       "bytes": 90609517
@@ -1485,7 +1485,7 @@
       "path": "results/episode_task_suite/research_directions/research_direction_taxonomy.json",
       "kind": "taxonomy",
       "surface": "repo_hf",
-      "shows": "Maps the original tasks to the four Ropedia research directions as direct/proxy/diagnostic.",
+      "shows": "Maps the walkthrough-backed tasks to the four Ropedia research directions as direct/proxy/diagnostic.",
       "exists": true,
       "bytes": 25046,
       "sha256": "0e3c442e5eb9057b04b1e8c8fa723dfde6f72e7fae1378d5ea022d93f7d25ca3"
@@ -1509,8 +1509,8 @@
       "surface": "repo_hf",
       "shows": "Stores the historical result bundle for provenance rows with minimal and neural baselines aligned to the same 20-task window/split setup.",
       "exists": true,
-      "bytes": 33402,
-      "sha256": "5a1051d25ceafe53c60dbd5b81d4b686a421c493ad09a462ad96bac100c5f3f3"
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+      "sha256": "d6d2f851325a691e77aed6d948f7355b16cf8d81ca35bf115e7309a7b7308efd"
     },
     {
       "id": "tier2_task_suite_json",
@@ -1520,8 +1520,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable provenance definitions, setup alignment, metrics, and public source paths; the file name is historical.",
       "exists": true,
-      "bytes": 33402,
-      "sha256": "5a1051d25ceafe53c60dbd5b81d4b686a421c493ad09a462ad96bac100c5f3f3"
+      "bytes": 33575,
+      "sha256": "d6d2f851325a691e77aed6d948f7355b16cf8d81ca35bf115e7309a7b7308efd"
     },
     {
       "id": "tier2_task_suite_chart",
@@ -1531,8 +1531,8 @@
       "surface": "website_hf",
       "shows": "Visual summary of the historical provenance baseline metrics inside the unified 20-task suite.",
       "exists": true,
-      "bytes": 5437,
-      "sha256": "3e35e476f559cd6188e5417e4d28c25efc130abafc9cab2d941bc77d559177a1"
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+      "sha256": "e9da29c57f42b29a7a05622fee1335089ac2b6fc9692a3b49fa5b753904db9dc"
     },
     {
       "id": "tier2_task_suite_builder",
@@ -1542,8 +1542,8 @@
       "surface": "repo_hf",
       "shows": "Regenerates the historical provenance rows from shared windows plus the local public-sample annotation HDF5; the script name is historical.",
       "exists": true,
-      "bytes": 47102,
-      "sha256": "3cddefaaeedd8efb65e6db956cbd13605e4a5b3772d98fa831d34fd6f92850de"
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+      "sha256": "569f05c1299f5186778ec75280188969fe1a5a76ae8553738fd44fc2faaab195"
     },
     {
       "id": "task_walkthroughs",
@@ -1564,8 +1564,8 @@
       "surface": "website_hf",
       "shows": "Presents the task suite and sample modality thumbnails with metrics generated from committed files.",
       "exists": true,
-      "bytes": 1903454,
-      "sha256": "6667eb856cf61ada9f868807b5d5c6ccde06e4f791b2f9dd567d98b71b307415"
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+      "sha256": "71b1ab150e952cf902488226c65b3822d8016974f63d111204c1eb1a7745faad"
     },
     {
       "id": "modality_atlas",
@@ -1672,7 +1672,7 @@
       "path": "results/omni_finetune/multi_episode_128_task_baselines/BASELINE_ALIGNMENT_REPORT.md",
       "kind": "scaleup_status",
       "surface": "repo_hf",
-      "shows": "Summarizes same-split simple and neural metadata baselines for the 12 original task ids, with unsupported markers for tasks that need missing raw 128 feature blocks.",
+      "shows": "Summarizes same-split simple and neural metadata baselines for the walkthrough-backed task ids, with unsupported markers for tasks that need missing raw 128 feature blocks.",
       "exists": true,
       "bytes": 2238,
       "sha256": "c70440aa502ec569a840159ab7e05b8e7d4ed70e0091ad9a4b2fb3fb0d3803c1"
@@ -1696,8 +1696,8 @@
       "surface": "repo_hf",
       "shows": "Reader-facing comparison of the single-episode task suite, 128-episode aligned baselines, Qwen3-Omni packages, and Cosmos3 future-window branch.",
       "exists": true,
-      "bytes": 15983,
-      "sha256": "4db248566972e811aac6ca06582f233414821624f00f9d4fc4a1b66b2e00401f"
+      "bytes": 15997,
+      "sha256": "c8296c51eb1d67d155b84e3a39f703642d30e855fee7ee7d6ca437966b5c760b"
     },
     {
       "id": "omni_model_comparison_json",
@@ -1707,8 +1707,8 @@
       "surface": "repo_hf",
       "shows": "Machine-readable comparison of the current result versions, per-task aligned baselines, verified Qwen3 packages, and Cosmos3 package.",
       "exists": true,
-      "bytes": 82088,
-      "sha256": "82ccc2932cad63a9ebad85da53e694b18ef626aa3720bda3ed5da30f3dc5e121"
+      "bytes": 82102,
+      "sha256": "6b246dbdb2685efdc9d0a92bb8c446a89523a1787ebc8a883805b4179e266dd1"
     },
     {
       "id": "cosmos3_nano_verified_summary",

data/episode128_task_model_radar.json

@@ -1,7 +1,7 @@
 {
   "title": "128-Episode 20-Task Radar",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T10:47:17+00:00",
+  "generated_at_utc": "2026-06-21T15:20:34+00:00",
   "description": "Selected 128-episode metadata/raw baselines plus verified Qwen3-Omni v6, Cosmos3-Super, and Cosmos3-Nano diagnostics. Every method has 20 records; numeric scores appear only where the public artifact produced that task target.",
   "task_count": 20,
   "method_count": 7,
@@ -192,7 +192,7 @@
       "label": "Action Recognition",
       "axis_label": "01 Action Recognition",
       "short_label": "Action",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -283,7 +283,7 @@
       "label": "Procedure Step Recognition",
       "axis_label": "02 Procedure Step Recognition",
       "short_label": "Step",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -374,7 +374,7 @@
       "label": "Action Boundary Detection",
       "axis_label": "03 Action Boundary Detection",
       "short_label": "Boundary",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -465,7 +465,7 @@
       "label": "Next-Action Prediction",
       "axis_label": "04 Next-Action Prediction",
       "short_label": "Next act",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -556,7 +556,7 @@
       "label": "Hand Trajectory Forecasting",
       "axis_label": "05 Hand Trajectory Forecasting",
       "short_label": "Hand traj",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "mpjpe",
       "metric_name": "MPJPE",
       "metric_direction": "lower",
@@ -647,7 +647,7 @@
       "label": "Contact State Prediction",
       "axis_label": "06 Contact State Prediction",
       "short_label": "Contact",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -738,7 +738,7 @@
       "label": "Object Relevance Prediction",
       "axis_label": "07 Object Relevance Prediction",
       "short_label": "Objects",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "micro_f1",
       "metric_name": "micro-F1",
       "metric_direction": "higher",
@@ -829,7 +829,7 @@
       "label": "Language Grounding",
       "axis_label": "08 Language Grounding",
       "short_label": "Language",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "mrr",
       "metric_name": "MRR",
       "metric_direction": "higher",
@@ -920,7 +920,7 @@
       "label": "Cross-Modal Retrieval",
       "axis_label": "09 Cross-Modal Retrieval",
       "short_label": "X-modal",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "mrr",
       "metric_name": "MRR",
       "metric_direction": "higher",
@@ -1011,7 +1011,7 @@
       "label": "Cross-Modal Reconstruction",
       "axis_label": "10 Cross-Modal Reconstruction",
       "short_label": "Recon",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "r2",
       "metric_name": "R2",
       "metric_direction": "higher",
@@ -1102,7 +1102,7 @@
       "label": "Temporal Order Verification",
       "axis_label": "11 Temporal Order Verification",
       "short_label": "Order",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "f1",
       "metric_name": "F1",
       "metric_direction": "higher",
@@ -1193,7 +1193,7 @@
       "label": "Multimodal Synchronization Detection",
       "axis_label": "12 Multimodal Synchronization Detection",
       "short_label": "Sync",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "f1",
       "metric_name": "F1",
       "metric_direction": "higher",
@@ -1284,7 +1284,7 @@
       "label": "Long-Horizon Next-Action Forecasting",
       "axis_label": "13 Long-Horizon Next-Action Forecasting",
       "short_label": "Long act",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -1375,7 +1375,7 @@
       "label": "Long-Horizon Next-Subtask Forecasting",
       "axis_label": "14 Long-Horizon Next-Subtask Forecasting",
       "short_label": "Long step",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -1466,7 +1466,7 @@
       "label": "Interaction Text Prediction",
       "axis_label": "15 Interaction Text Prediction",
       "short_label": "Interact txt",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -1557,7 +1557,7 @@
       "label": "Action-Object Relation Prediction",
       "axis_label": "16 Action-Object Relation Prediction",
       "short_label": "Act+obj",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -1648,7 +1648,7 @@
       "label": "Future Object-Set Forecasting",
       "axis_label": "17 Future Object-Set Forecasting",
       "short_label": "Future obj",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "micro_f1",
       "metric_name": "micro-F1",
       "metric_direction": "higher",
@@ -1739,7 +1739,7 @@
       "label": "IMU-to-Hand Pose Reconstruction",
       "axis_label": "18 IMU-to-Hand Pose Reconstruction",
       "short_label": "IMU->hand",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "mae",
       "metric_name": "MAE",
       "metric_direction": "lower",
@@ -1830,7 +1830,7 @@
       "label": "Camera-View Synchronization Retrieval",
       "axis_label": "19 Camera-View Synchronization Retrieval",
       "short_label": "Cam sync",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "mrr",
       "metric_name": "MRR",
       "metric_direction": "higher",
@@ -1921,7 +1921,7 @@
       "label": "Time-to-Next-Transition Regression",
       "axis_label": "20 Time-to-Next-Transition Regression",
       "short_label": "Time2bdry",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "mae",
       "metric_name": "MAE frames",
       "metric_direction": "lower",

data/evaluation_protocol.json

@@ -2,7 +2,7 @@
   "title": "Ropedia Xperience-10M Task Suite Evaluation Protocol",
   "status": "pass",
   "version": "2026-06-01",
-  "generated_at_utc": "2026-06-21T14:40:33+00:00",
+  "generated_at_utc": "2026-06-21T15:20:33+00:00",
   "source_files": [
     "docs/data/summary_metrics.json",
     "results/episode_task_suite/summary_report.json",
@@ -26,8 +26,8 @@
   "task_suite": {
     "status": "unified_public_sample_suite",
     "task_count": 20,
-    "original_public_sample_tasks": 12,
-    "additional_public_sample_tasks": 8,
+    "public_framing": "all 20 public-sample task contracts are presented as one suite",
+    "legacy_provenance_rows": 8,
     "unified_results": "docs/data/task_suite_20.json",
     "legacy_additional_task_result_path": "docs/data/tier2_task_suite.json",
     "legacy_path_note": "The tier2_task_suite path is retained for stable links only; it is provenance inside the same 20-task suite."
@@ -82,7 +82,7 @@
     {
       "task": "timeline_action",
       "task_display_name": "Action Recognition",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "family": "supervised classification",
       "unit": "single window",
       "input": "current 20-frame all-feature window",
@@ -105,7 +105,7 @@
     {
       "task": "timeline_subtask",
       "task_display_name": "Procedure Step Recognition",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "family": "supervised classification",
       "unit": "single window",
       "input": "current 20-frame all-feature window",
@@ -128,7 +128,7 @@
     {
       "task": "transition_detection",
       "task_display_name": "Action Boundary Detection",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "family": "temporal diagnostic",
       "unit": "single window",
       "input": "current 20-frame all-feature window",
@@ -151,7 +151,7 @@
     {
       "task": "next_action",
       "task_display_name": "Next-Action Prediction",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "family": "short-horizon prediction",
       "unit": "single window",
       "input": "current 20-frame all-feature window at time t",
@@ -174,7 +174,7 @@
     {
       "task": "hand_trajectory_forecast",
       "task_display_name": "Hand Trajectory Forecasting",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "family": "trajectory regression",
       "unit": "single window",
       "input": "current all-feature window",
@@ -197,7 +197,7 @@
     {
       "task": "contact_prediction",
       "task_display_name": "Contact State Prediction",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "family": "binary classification",
       "unit": "single window",
       "input": "non-contact and non-caption feature blocks",
@@ -220,7 +220,7 @@
     {
       "task": "object_relevance",
       "task_display_name": "Object Relevance Prediction",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "family": "multi-label classification",
       "unit": "single window",
       "input": "non-caption feature blocks",
@@ -243,7 +243,7 @@
     {
       "task": "caption_grounding",
       "task_display_name": "Language Grounding",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "family": "retrieval",
       "unit": "caption query",
       "input": "caption object/interaction query plus candidate sensor windows",
@@ -266,7 +266,7 @@
     {
       "task": "cross_modal_retrieval",
       "task_display_name": "Cross-Modal Retrieval",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "family": "retrieval",
       "unit": "sensor query",
       "input": "motion, IMU, and camera query features",
@@ -289,7 +289,7 @@
     {
       "task": "modality_reconstruction",
       "task_display_name": "Cross-Modal Reconstruction",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "family": "cross-modal regression",
       "unit": "single window",
       "input": "motion, IMU, and camera features",
@@ -311,7 +311,7 @@
     {
       "task": "temporal_order",
       "task_display_name": "Temporal Order Verification",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "family": "pairwise diagnostic",
       "unit": "adjacent window pair",
       "input": "two adjacent windows",
@@ -334,7 +334,7 @@
     {
       "task": "misalignment_detection",
       "task_display_name": "Multimodal Synchronization Detection",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "family": "pairwise diagnostic",
       "unit": "paired modality window",
       "input": "motion side plus visual/depth side",
@@ -357,7 +357,7 @@
     {
       "task": "long_horizon_next_action",
       "task_display_name": "Long-Horizon Next-Action Forecasting",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "family": "classification",
       "unit": "single aligned window",
       "input": "Current 20-frame non-caption multimodal window.",
@@ -375,7 +375,7 @@
     {
       "task": "next_subtask_forecast",
       "task_display_name": "Long-Horizon Next-Subtask Forecasting",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "family": "classification",
       "unit": "single aligned window",
       "input": "Current 20-frame non-caption multimodal window.",
@@ -393,7 +393,7 @@
     {
       "task": "interaction_text_prediction",
       "task_display_name": "Interaction Text Prediction",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "family": "classification",
       "unit": "single aligned window",
       "input": "Current 20-frame sensor window with caption-text features removed.",
@@ -411,7 +411,7 @@
     {
       "task": "action_object_relation",
       "task_display_name": "Action-Object Relation Prediction",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "family": "classification",
       "unit": "single aligned window",
       "input": "Current 20-frame sensor window with caption-text features removed.",
@@ -429,7 +429,7 @@
     {
       "task": "object_set_forecast",
       "task_display_name": "Future Object-Set Forecasting",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "family": "multi_label",
       "unit": "single aligned window",
       "input": "Current 20-frame sensor window with caption-text features removed.",
@@ -447,7 +447,7 @@
     {
       "task": "imu_to_hand_pose",
       "task_display_name": "IMU-to-Hand Pose Reconstruction",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "family": "regression",
       "unit": "single aligned window",
       "input": "Current IMU acceleration/gyroscope feature block only.",
@@ -465,7 +465,7 @@
     {
       "task": "camera_view_sync_retrieval",
       "task_display_name": "Camera-View Synchronization Retrieval",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "family": "retrieval",
       "unit": "held-out query window",
       "input": "Fisheye camera-1 feature query projected into fisheye camera-3 feature space.",
@@ -483,7 +483,7 @@
     {
       "task": "time_to_transition",
       "task_display_name": "Time-to-Next-Transition Regression",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "family": "regression",
       "unit": "single aligned window",
       "input": "Current 20-frame non-caption multimodal window.",

data/figure_index.json

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Figure Index",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T14:40:33+00:00",
+  "generated_at_utc": "2026-06-21T15:19:00+00:00",
   "scope": "Public figures, diagrams, charts, and derived modality thumbnails. Raw Xperience-10M videos, annotations, RRD files, and Qwen weights are excluded.",
   "figure_count": 29,
   "figures": [
@@ -60,12 +60,12 @@
       "id": "task_suite_infographic",
       "title": "Original task-suite infographic",
       "path": "docs/assets/task_suite_infographic.png",
-      "role": "Primary visual map of the original task families, verified metrics, and sample modalities; the unified public suite is now documented as 20 tasks.",
+      "role": "Primary visual map of the walkthrough-backed task families, verified metrics, and sample modalities; the unified public suite is documented as 20 tasks.",
       "source_script": "scripts/render_task_suite_infographic.py",
       "surface": "README, website, HF Space, artifact dataset, model card",
       "exists": true,
-      "bytes": 1903454,
-      "sha256": "6667eb856cf61ada9f868807b5d5c6ccde06e4f791b2f9dd567d98b71b307415",
+      "bytes": 1897278,
+      "sha256": "71b1ab150e952cf902488226c65b3822d8016974f63d111204c1eb1a7745faad",
       "dimensions": {
         "format": "PNG",
         "width": 1800,
@@ -162,7 +162,7 @@
       "id": "task_architectures",
       "title": "Minimal and neural task architecture map",
       "path": "docs/assets/task_architectures.png",
-      "role": "Minimal and neural heads for the original task contracts and shared feature contracts.",
+      "role": "Minimal and neural heads for the walkthrough-backed task contracts and shared feature contracts.",
       "source_script": "scripts/render_overview_figures.py",
       "surface": "README, website, HF artifact dataset, model card",
       "exists": true,
@@ -392,8 +392,8 @@
       "source_script": "scripts/tier2_task_suite.py",
       "surface": "website unified task section, README, HF mirrors",
       "exists": true,
-      "bytes": 5437,
-      "sha256": "3e35e476f559cd6188e5417e4d28c25efc130abafc9cab2d941bc77d559177a1",
+      "bytes": 5453,
+      "sha256": "e9da29c57f42b29a7a05622fee1335089ac2b6fc9692a3b49fa5b753904db9dc",
       "dimensions": {
         "format": "SVG",
         "width": 1440,

data/omni_model_comparison.json

@@ -1,12 +1,12 @@
 {
   "title": "Ropedia Xperience-10M Current Result Versions and Model Groups",
-  "generated_at_utc": "2026-06-21T10:47:04+00:00",
+  "generated_at_utc": "2026-06-21T15:17:00+00:00",
   "status": "pass",
   "version_count": 3,
   "model_group_count": 5,
   "comparison_rule": "Compare only rows with the same scope and target. Single-episode raw-feature metrics, 128-episode metadata baselines, Qwen3 structured JSON metrics, and the two Cosmos3 targets answer different questions: Nano future-window retrieval versus Super structured JSON Reasoner evaluation.",
   "version_reading_notes": [
-    "Version 1 is the public-sample 20-task surface: original core heads, tasks 13-20, and the 180-row method-task matrix.",
+    "Version 1 is the public-sample 20-task surface: unified task heads, historical provenance rows, and the 180-row method-task matrix.",
     "Version 2 is the selected 128-episode same-split simple/NN baseline alignment.",
     "The selected-128 model-diagnostic group contains the current Qwen3-Omni LoRA JSON-task row, Cosmos3-Nano future-window compatibility result, Cosmos3-Super Reasoner base-weight JSON-task evaluation, and the separate Cosmos3-Super Forward-Dynamics LoRA adapter artifact."
   ],

data/project_brief.json

@@ -52,7 +52,7 @@
     "Open EVALUATION_PROTOCOL.md before comparing task scores.",
     "Use RESEARCH_TAKEAWAYS.md for the current metric interpretation.",
     "Inspect results/episode_task_suite/feature_manifest.json to understand one model input.",
-    "Use TASK_SUITE_20.md and docs/data/task_suite_20.json to read the unified 20-task suite; the historical docs/data/tier2_task_suite.json path stores the tasks 13-20 result bundle.",
+    "Use TASK_SUITE_20.md and docs/data/task_suite_20.json to read the unified 20-task suite; the historical docs/data/tier2_task_suite.json path is retained only for provenance inside that suite.",
     "Use docs/data/omni_finetune_verified_result.json for the current multi-episode Qwen3-Omni pilot result."
   ],
   "scope_boundary": "The public sample is enough to build and verify task definitions, feature contracts, metrics, visualization, and baseline code. The final multi-episode Qwen3-Omni diagnostic result verifies the training loop and strict-JSON output reliability, but does not yet show strong action/subtask model quality.",

data/project_manifest.json

@@ -23,9 +23,8 @@
     "qwen3_omni_json_quality_target_met": true,
     "qwen3_omni_lora_adapter_repo": "https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep",
     "task_count": 20,
-    "original_public_sample_task_count": 12,
-    "additional_public_sample_task_count": 8,
-    "legacy_tasks_13_to_20_result_path": "docs/data/tier2_task_suite.json"
+    "task_surface_framing": "unified_20_task_suite",
+    "legacy_provenance_result_path": "docs/data/tier2_task_suite.json"
   },
   "public_surfaces": {
     "github_repo": "https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite",
@@ -96,7 +95,7 @@
     "task_walkthroughs": "docs/data/task_walkthroughs.json",
     "task_suite_20": "TASK_SUITE_20.md",
     "task_suite_20_json": "docs/data/task_suite_20.json",
-    "tasks_13_to_20_result_bundle": "docs/data/tier2_task_suite.json"
+    "historical_provenance_result_bundle": "docs/data/tier2_task_suite.json"
   },
   "citation_files": {
     "citation_cff": "CITATION.cff",

data/project_packet.json

@@ -15,9 +15,8 @@
     "cosmos3_super_forward_dynamics_lora_status": "The first Cosmos3-Super fine-tuned adapter branch is verified as a forward-dynamics LoRA over camera-pose proxy targets; it reports loss metrics, not JSON action-label accuracy.",
     "task_suite_enhancement_128_status": "Current no-new-episode enhancement pack recommends multiscale_20s10_40s20_80s40, hierarchical action/subtask targets, label-normalized scoring, and raw-feature shards before adding more episodes.",
     "task_count": 20,
-    "original_public_sample_task_count": 12,
-    "additional_public_sample_task_count": 8,
-    "legacy_tasks_13_to_20_result_path": "docs/data/tier2_task_suite.json"
+    "task_surface_framing": "unified_20_task_suite",
+    "legacy_provenance_result_path": "docs/data/tier2_task_suite.json"
   },
   "reading_path": [
     {
@@ -110,7 +109,7 @@
         "results/episode_task_suite/neural_mlp/",
         "docs/data/summary_metrics.json"
       ],
-      "readout": "The unified suite has 20 task contracts; tasks 1-12 have walkthroughs and neural MLP heads, and tasks 13-20 have aligned minimal/neural result bundles under the historical tier2_task_suite path."
+      "readout": "The unified suite has 20 task contracts in one task surface. Walkthrough-backed tasks, aligned minimal/neural result bundles, and historical tier2_task_suite provenance paths are all linked from TASK_SUITE_20.md and docs/data/task_suite_20.json."
     },
     {
       "step": 8,

data/public_surface_qa.json

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Public Project Surface",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T14:46:49+00:00",
+  "generated_at_utc": "2026-06-21T15:21:42+00:00",
   "scope": "Repo README, GitHub Pages HTML, Hugging Face Space card, artifact dataset card, and model card.",
   "checks": [
     {
@@ -33,12 +33,12 @@
         "source_alignment": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-21T13:32:47+00:00"
+          "generated_at_utc": "2026-06-21T14:46:49+00:00"
         },
         "scale_up_status": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-21T13:32:50+00:00"
+          "generated_at_utc": "2026-06-21T14:47:03+00:00"
         },
         "publication_package": {
           "exists": true,
@@ -48,7 +48,7 @@
         "mirror_parity": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-21T14:13:08+00:00"
+          "generated_at_utc": "2026-06-21T14:53:27+00:00"
         }
       },
       "failures": {}
@@ -96,7 +96,7 @@
       "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": 20,
-        "Xperience-10M": 167,
+        "Xperience-10M": 166,
         "20-task": 100,
         "Qwen3-Omni": 245,
         "128-episode pilot": 1
@@ -137,11 +137,11 @@
         "data/unified_task_model_radar.json": 21,
         "data/single_episode_task_model_radar.json": 17,
         "data/episode128_task_model_radar.json": 16,
-        "data/task_method_20_result_matrix.json": 24,
+        "data/task_method_20_result_matrix.json": 25,
         "data/task_method_20_gap_audit.json": 23,
         "data/language_versions.json": 3,
         "assets/charts/two_evidence_line_map.svg": 5,
-        "assets/charts/unified_task_model_radar.svg": 17,
+        "assets/charts/unified_task_model_radar.svg": 18,
         "assets/charts/single_episode_task_model_radar.svg": 19,
         "assets/charts/episode128_task_model_radar.svg": 19,
         "data/tier2_task_suite.json": 11

data/quality_gates.json

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Release Checks",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T14:46:48+00:00",
+  "generated_at_utc": "2026-06-21T15:21:42+00:00",
   "rule": "A release is current when the automated reports pass and the live GitHub/Hugging Face mirrors are verified after publishing.",
   "automated_gates": [
     {

data/reproducibility_matrix.json

@@ -39,7 +39,7 @@
       "id": "original_task_suite",
       "status": "reproducible",
       "command": "python scripts/episode_task_suite.py --workspace $WORKSPACE --include-neural",
-      "expected": "original task metrics, predictions, manifests, and neural_mlp task-head artifacts",
+      "expected": "walkthrough-backed task metrics, predictions, manifests, and neural_mlp task-head artifacts",
       "boundary": "8,546-dimensional multimodal window contract"
     },
     {
@@ -50,11 +50,11 @@
       "boundary": "single-episode probes, not full research-direction solutions"
     },
     {
-      "id": "tasks_13_to_20_and_unified_index",
+      "id": "unified_20_task_index",
       "status": "reproducible",
       "command": "python scripts/tier2_task_suite.py && python scripts/build_unified_task_suite.py && python scripts/build_unified_task_model_radar.py",
-      "expected": "tasks 13-20 metrics, prediction/rank artifacts, TASK_SUITE_20.md, docs/data/task_suite_20.json, docs/data/tier2_task_suite.json, docs/assets/charts/tier2_task_suite.svg, docs/data/unified_task_model_radar.json, and docs/assets/charts/unified_task_model_radar.svg",
-      "boundary": "requires local public-sample annotation.hdf5 plus HOMIE Toolkit or h5py for tasks 13-20; raw HDF5 and MP4 files are not redistributed"
+      "expected": "unified 20-task metrics, prediction/rank artifacts, TASK_SUITE_20.md, docs/data/task_suite_20.json, docs/data/tier2_task_suite.json, docs/assets/charts/tier2_task_suite.svg, docs/data/unified_task_model_radar.json, and docs/assets/charts/unified_task_model_radar.svg",
+      "boundary": "requires local public-sample annotation.hdf5 plus HOMIE Toolkit or h5py for full public-task regeneration; raw HDF5 and MP4 files are not redistributed"
     },
     {
       "id": "source_alignment_audit",

data/research_takeaways.json

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Research Takeaways",
   "status": "pass",
-  "generated_at_utc": "2026-06-20T21:27:21+00:00",
+  "generated_at_utc": "2026-06-21T15:18:59+00:00",
   "source_files": [
     "docs/data/summary_metrics.json",
     "results/episode_task_suite/summary_report.json",
@@ -133,7 +133,7 @@
     {
       "id": "audio_contribution_is_task_specific",
       "title": "Audio helps some tasks and hurts others on the public sample",
-      "readout": "Audio improves the primary metric on 6 of the original task contracts, while raw log-mel replacement improves over the current handcrafted block on 6 of those contracts. The largest current-audio gain appears in feature reconstruction, not in action classification.",
+      "readout": "Audio improves the primary metric on 6 walkthrough-backed task contracts, while raw log-mel replacement improves over the current handcrafted block on 6 of those contracts. The largest current-audio gain appears in feature reconstruction, not in action classification.",
       "evidence": [
         {
           "label": "tasks_where_current_audio_improves",

data/scope_claims_audit.json

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-21T14:47:03+00:00",
+  "generated_at_utc": "2026-06-21T15:23:13+00:00",
   "summary": {
     "qwen3_omni_verified_diagnostic_pilot": true,
     "dataset_manifest_num_episodes": 119,

data/single_episode_task_model_radar.json

@@ -1,7 +1,7 @@
 {
   "title": "Single-Episode 20-Task Radar",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T10:47:17+00:00",
+  "generated_at_utc": "2026-06-21T15:20:34+00:00",
   "description": "Minimal and Neural MLP baselines on the one public sample episode, both scored on all 20 task contracts.",
   "task_count": 20,
   "method_count": 2,
@@ -73,7 +73,7 @@
       "label": "Action Recognition",
       "axis_label": "01 Action Recognition",
       "short_label": "Action",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -107,7 +107,7 @@
       "label": "Procedure Step Recognition",
       "axis_label": "02 Procedure Step Recognition",
       "short_label": "Step",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -141,7 +141,7 @@
       "label": "Action Boundary Detection",
       "axis_label": "03 Action Boundary Detection",
       "short_label": "Boundary",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -175,7 +175,7 @@
       "label": "Next-Action Prediction",
       "axis_label": "04 Next-Action Prediction",
       "short_label": "Next act",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -209,7 +209,7 @@
       "label": "Hand Trajectory Forecasting",
       "axis_label": "05 Hand Trajectory Forecasting",
       "short_label": "Hand traj",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "mpjpe",
       "metric_name": "MPJPE",
       "metric_direction": "lower",
@@ -243,7 +243,7 @@
       "label": "Contact State Prediction",
       "axis_label": "06 Contact State Prediction",
       "short_label": "Contact",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -277,7 +277,7 @@
       "label": "Object Relevance Prediction",
       "axis_label": "07 Object Relevance Prediction",
       "short_label": "Objects",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "micro_f1",
       "metric_name": "micro-F1",
       "metric_direction": "higher",
@@ -311,7 +311,7 @@
       "label": "Language Grounding",
       "axis_label": "08 Language Grounding",
       "short_label": "Language",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "mrr",
       "metric_name": "MRR",
       "metric_direction": "higher",
@@ -345,7 +345,7 @@
       "label": "Cross-Modal Retrieval",
       "axis_label": "09 Cross-Modal Retrieval",
       "short_label": "X-modal",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "mrr",
       "metric_name": "MRR",
       "metric_direction": "higher",
@@ -379,7 +379,7 @@
       "label": "Cross-Modal Reconstruction",
       "axis_label": "10 Cross-Modal Reconstruction",
       "short_label": "Recon",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "r2",
       "metric_name": "R2",
       "metric_direction": "higher",
@@ -413,7 +413,7 @@
       "label": "Temporal Order Verification",
       "axis_label": "11 Temporal Order Verification",
       "short_label": "Order",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "f1",
       "metric_name": "F1",
       "metric_direction": "higher",
@@ -447,7 +447,7 @@
       "label": "Multimodal Synchronization Detection",
       "axis_label": "12 Multimodal Synchronization Detection",
       "short_label": "Sync",
-      "origin": "original_public_sample_tasks",
+      "provenance_source": "walkthrough_backed_task_contract",
       "metric_key": "f1",
       "metric_name": "F1",
       "metric_direction": "higher",
@@ -481,7 +481,7 @@
       "label": "Long-Horizon Next-Action Forecasting",
       "axis_label": "13 Long-Horizon Next-Action Forecasting",
       "short_label": "Long act",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -515,7 +515,7 @@
       "label": "Long-Horizon Next-Subtask Forecasting",
       "axis_label": "14 Long-Horizon Next-Subtask Forecasting",
       "short_label": "Long step",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -549,7 +549,7 @@
       "label": "Interaction Text Prediction",
       "axis_label": "15 Interaction Text Prediction",
       "short_label": "Interact txt",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -583,7 +583,7 @@
       "label": "Action-Object Relation Prediction",
       "axis_label": "16 Action-Object Relation Prediction",
       "short_label": "Act+obj",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "macro_f1",
       "metric_name": "macro-F1",
       "metric_direction": "higher",
@@ -617,7 +617,7 @@
       "label": "Future Object-Set Forecasting",
       "axis_label": "17 Future Object-Set Forecasting",
       "short_label": "Future obj",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "micro_f1",
       "metric_name": "micro-F1",
       "metric_direction": "higher",
@@ -651,7 +651,7 @@
       "label": "IMU-to-Hand Pose Reconstruction",
       "axis_label": "18 IMU-to-Hand Pose Reconstruction",
       "short_label": "IMU->hand",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "mae",
       "metric_name": "MAE",
       "metric_direction": "lower",
@@ -685,7 +685,7 @@
       "label": "Camera-View Synchronization Retrieval",
       "axis_label": "19 Camera-View Synchronization Retrieval",
       "short_label": "Cam sync",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "mrr",
       "metric_name": "MRR",
       "metric_direction": "higher",
@@ -719,7 +719,7 @@
       "label": "Time-to-Next-Transition Regression",
       "axis_label": "20 Time-to-Next-Transition Regression",
       "short_label": "Time2bdry",
-      "origin": "additional_public_sample_tasks",
+      "provenance_source": "historical_result_bundle",
       "metric_key": "mae",
       "metric_name": "MAE frames",
       "metric_direction": "lower",

data/source_alignment_audit.json

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Source Alignment Note",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T14:46:49+00:00",
+  "generated_at_utc": "2026-06-21T15:21:55+00:00",
   "alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
   "alignment_summary": {
     "full_dataset_repo": "ropedia-ai/xperience-10m",

data/task_method_20_gap_audit.json

@@ -1,5 +1,5 @@
 {
-  "generated_at_utc": "2026-06-21T08:38:20+00:00",
+  "generated_at_utc": "2026-06-21T15:21:42+00:00",
   "immediate_actions": [
     {
       "artifact": "docs/data/task_method_20_gap_audit.json",

data/task_method_20_result_matrix.json

@@ -1,7 +1,7 @@
 {
   "title": "Task Method 20-Result Matrix",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T10:47:17+00:00",
+  "generated_at_utc": "2026-06-21T15:20:34+00:00",
   "task_count": 20,
   "method_count": 9,
   "method_task_record_count": 180,

data/task_suite_20.json

@@ -1,12 +1,12 @@
 {
   "title": "Ropedia Xperience-10M Unified 20-Task Suite",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T14:40:33+00:00",
+  "generated_at_utc": "2026-06-21T15:21:12+00:00",
   "task_count": 20,
-  "task_count_breakdown": {
-    "original_public_sample_tasks": 12,
-    "additional_public_sample_tasks": 8,
-    "total_unified_tasks": 20
+  "task_count_summary": {
+    "total_unified_tasks": 20,
+    "public_framing": "all 20 task contracts are presented as one suite",
+    "legacy_provenance_rows": 8
   },
   "unification_policy": {
     "public_framing": "The suite is presented as one 20-task benchmark surface. All task contracts share the same window, split, feature, baseline, and leakage-control language.",
@@ -21,7 +21,7 @@
     "window_frames": 20,
     "stride_frames": 5,
     "split_policy": "single_episode_chronological_70_30",
-    "raw_hdf5_required_for_tasks_13_20_regeneration": true,
+    "raw_hdf5_required_for_full_public_regeneration": true,
     "raw_data_redistributed": false
   },
   "setup_alignment": {
@@ -47,8 +47,8 @@
       "task_id": "timeline_action",
       "task_display_name": "Action Recognition",
       "research_name": "Egocentric Action Recognition",
-      "origin": "original_public_sample_tasks",
-      "origin_count_label": "original task",
+      "provenance_source": "walkthrough_backed_task_contract",
+      "origin_count_label": "unified task",
       "family": "supervised",
       "architecture_family": "multiclass classifier",
       "primary_direction": "C. Egocentric Vision & Interaction",
@@ -82,8 +82,8 @@
       "task_id": "timeline_subtask",
       "task_display_name": "Procedure Step Recognition",
       "research_name": "Temporal Subtask Recognition",
-      "origin": "original_public_sample_tasks",
-      "origin_count_label": "original task",
+      "provenance_source": "walkthrough_backed_task_contract",
+      "origin_count_label": "unified task",
       "family": "supervised",
       "architecture_family": "multiclass classifier",
       "primary_direction": "C. Egocentric Vision & Interaction",
@@ -117,8 +117,8 @@
       "task_id": "transition_detection",
       "task_display_name": "Action Boundary Detection",
       "research_name": "Temporal Action Segmentation",
-      "origin": "original_public_sample_tasks",
-      "origin_count_label": "original task",
+      "provenance_source": "walkthrough_backed_task_contract",
+      "origin_count_label": "unified task",
       "family": "diagnostic",
       "architecture_family": "binary classifier",
       "primary_direction": "C. Egocentric Vision & Interaction",
@@ -152,8 +152,8 @@
       "task_id": "next_action",
       "task_display_name": "Next-Action Prediction",
       "research_name": "Short-Horizon Intention Prediction",
-      "origin": "original_public_sample_tasks",
-      "origin_count_label": "original task",
+      "provenance_source": "walkthrough_backed_task_contract",
+      "origin_count_label": "unified task",
       "family": "supervised",
       "architecture_family": "future-label classifier",
       "primary_direction": "C. Egocentric Vision & Interaction",
@@ -187,8 +187,8 @@
       "task_id": "hand_trajectory_forecast",
       "task_display_name": "Hand Trajectory Forecasting",
       "research_name": "3D Hand Motion Forecasting",
-      "origin": "original_public_sample_tasks",
-      "origin_count_label": "original task",
+      "provenance_source": "walkthrough_backed_task_contract",
+      "origin_count_label": "unified task",
       "family": "forecast",
       "architecture_family": "continuous regressor",
       "primary_direction": "A. Human Modeling & Motion Understanding",
@@ -220,8 +220,8 @@
       "task_id": "contact_prediction",
       "task_display_name": "Contact State Prediction",
       "research_name": "Human-Object Contact Prediction",
-      "origin": "original_public_sample_tasks",
-      "origin_count_label": "original task",
+      "provenance_source": "walkthrough_backed_task_contract",
+      "origin_count_label": "unified task",
       "family": "supervised",
       "architecture_family": "binary classifier",
       "primary_direction": "A. Human Modeling & Motion Understanding",
@@ -255,8 +255,8 @@
       "task_id": "object_relevance",
       "task_display_name": "Object Relevance Prediction",
       "research_name": "Object-Centric Interaction Recognition",
-      "origin": "original_public_sample_tasks",
-      "origin_count_label": "original task",
+      "provenance_source": "walkthrough_backed_task_contract",
+      "origin_count_label": "unified task",
       "family": "supervised",
       "architecture_family": "multi-label classifier",
       "primary_direction": "C. Egocentric Vision & Interaction",
@@ -288,8 +288,8 @@
       "task_id": "caption_grounding",
       "task_display_name": "Language Grounding",
       "research_name": "Language-to-Moment Grounding",
-      "origin": "original_public_sample_tasks",
-      "origin_count_label": "original task",
+      "provenance_source": "walkthrough_backed_task_contract",
+      "origin_count_label": "unified task",
       "family": "retrieval",
       "architecture_family": "retrieval ranker",
       "primary_direction": "C. Egocentric Vision & Interaction",
@@ -321,8 +321,8 @@
       "task_id": "cross_modal_retrieval",
       "task_display_name": "Cross-Modal Retrieval",
       "research_name": "Multimodal Representation Retrieval",
-      "origin": "original_public_sample_tasks",
-      "origin_count_label": "original task",
+      "provenance_source": "walkthrough_backed_task_contract",
+      "origin_count_label": "unified task",
       "family": "retrieval",
       "architecture_family": "two-tower retrieval head",
       "primary_direction": "D. Scene Reconstruction & World Modeling",
@@ -354,8 +354,8 @@
       "task_id": "modality_reconstruction",
       "task_display_name": "Cross-Modal Reconstruction",
       "research_name": "Modality Feature Reconstruction",
-      "origin": "original_public_sample_tasks",
-      "origin_count_label": "original task",
+      "provenance_source": "walkthrough_backed_task_contract",
+      "origin_count_label": "unified task",
       "family": "forecast",
       "architecture_family": "feature regressor",
       "primary_direction": "B. 3D/4D Reconstruction & Neural Rendering",
@@ -386,8 +386,8 @@
       "task_id": "temporal_order",
       "task_display_name": "Temporal Order Verification",
       "research_name": "Temporal Order Verification",
-      "origin": "original_public_sample_tasks",
-      "origin_count_label": "original task",
+      "provenance_source": "walkthrough_backed_task_contract",
+      "origin_count_label": "unified task",
       "family": "diagnostic",
       "architecture_family": "pairwise classifier",
       "primary_direction": "D. Scene Reconstruction & World Modeling",
@@ -419,8 +419,8 @@
       "task_id": "misalignment_detection",
       "task_display_name": "Multimodal Synchronization Detection",
       "research_name": "Cross-Modal Misalignment Detection",
-      "origin": "original_public_sample_tasks",
-      "origin_count_label": "original task",
+      "provenance_source": "walkthrough_backed_task_contract",
+      "origin_count_label": "unified task",
       "family": "diagnostic",
       "architecture_family": "pairwise classifier",
       "primary_direction": "B. 3D/4D Reconstruction & Neural Rendering",
@@ -452,8 +452,8 @@
       "task_id": "long_horizon_next_action",
       "task_display_name": "Long-Horizon Next-Action Forecasting",
       "research_name": "Long-Horizon Next-Action Forecasting",
-      "origin": "additional_public_sample_tasks",
-      "origin_count_label": "additional task",
+      "provenance_source": "historical_result_bundle",
+      "origin_count_label": "unified task",
       "family": "classification",
       "architecture_family": "minimal_softmax",
       "primary_direction": "sample-supported extension",
@@ -487,8 +487,8 @@
       "task_id": "next_subtask_forecast",
       "task_display_name": "Long-Horizon Next-Subtask Forecasting",
       "research_name": "Long-Horizon Next-Subtask Forecasting",
-      "origin": "additional_public_sample_tasks",
-      "origin_count_label": "additional task",
+      "provenance_source": "historical_result_bundle",
+      "origin_count_label": "unified task",
       "family": "classification",
       "architecture_family": "minimal_softmax",
       "primary_direction": "sample-supported extension",
@@ -522,8 +522,8 @@
       "task_id": "interaction_text_prediction",
       "task_display_name": "Interaction Text Prediction",
       "research_name": "Interaction Text Prediction",
-      "origin": "additional_public_sample_tasks",
-      "origin_count_label": "additional task",
+      "provenance_source": "historical_result_bundle",
+      "origin_count_label": "unified task",
       "family": "classification",
       "architecture_family": "minimal_softmax",
       "primary_direction": "sample-supported extension",
@@ -557,8 +557,8 @@
       "task_id": "action_object_relation",
       "task_display_name": "Action-Object Relation Prediction",
       "research_name": "Action-Object Relation Prediction",
-      "origin": "additional_public_sample_tasks",
-      "origin_count_label": "additional task",
+      "provenance_source": "historical_result_bundle",
+      "origin_count_label": "unified task",
       "family": "classification",
       "architecture_family": "minimal_softmax",
       "primary_direction": "sample-supported extension",
@@ -592,8 +592,8 @@
       "task_id": "object_set_forecast",
       "task_display_name": "Future Object-Set Forecasting",
       "research_name": "Future Object-Set Forecasting",
-      "origin": "additional_public_sample_tasks",
-      "origin_count_label": "additional task",
+      "provenance_source": "historical_result_bundle",
+      "origin_count_label": "unified task",
       "family": "multi_label",
       "architecture_family": "minimal_ridge_multilabel",
       "primary_direction": "sample-supported extension",
@@ -625,8 +625,8 @@
       "task_id": "imu_to_hand_pose",
       "task_display_name": "IMU-to-Hand Pose Reconstruction",
       "research_name": "IMU-to-Hand Pose Reconstruction",
-      "origin": "additional_public_sample_tasks",
-      "origin_count_label": "additional task",
+      "provenance_source": "historical_result_bundle",
+      "origin_count_label": "unified task",
       "family": "regression",
       "architecture_family": "minimal_ridge_regression",
       "primary_direction": "sample-supported extension",
@@ -658,8 +658,8 @@
       "task_id": "camera_view_sync_retrieval",
       "task_display_name": "Camera-View Synchronization Retrieval",
       "research_name": "Camera-View Synchronization Retrieval",
-      "origin": "additional_public_sample_tasks",
-      "origin_count_label": "additional task",
+      "provenance_source": "historical_result_bundle",
+      "origin_count_label": "unified task",
       "family": "retrieval",
       "architecture_family": "minimal_ridge_projection_cosine_retrieval",
       "primary_direction": "sample-supported extension",
@@ -690,8 +690,8 @@
       "task_id": "time_to_transition",
       "task_display_name": "Time-to-Next-Transition Regression",
       "research_name": "Time-to-Next-Transition Regression",
-      "origin": "additional_public_sample_tasks",
-      "origin_count_label": "additional task",
+      "provenance_source": "historical_result_bundle",
+      "origin_count_label": "unified task",
       "family": "regression",
       "architecture_family": "minimal_ridge_regression",
       "primary_direction": "sample-supported extension",

data/task_surface_integrity.json

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-21T14:45:00+00:00",
+  "generated_at_utc": "2026-06-21T15:21:55+00:00",
   "summary": {
     "original_walkthrough_task_count": 12,
     "expected_original_walkthrough_task_count": 12,

data/tier2_task_suite.json

@@ -2,13 +2,12 @@
   "title": "Ropedia Xperience-10M Unified 20-Task Provenance Bundle",
   "status": "pass",
   "generated_at_utc": "2026-06-16T06:25:58+00:00",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "legacy_path_note": "The tier2_task_suite file and directory names are retained for stable public links; this bundle is provenance inside the unified 20-task suite, not a separate public tier.",
-  "integrated_with_tasks_1_to_12": {
-    "tasks_1_to_12_count": 12,
-    "additional_task_count": 8,
-    "combined_task_count": 20,
-    "tasks_1_to_12_metrics": "docs/data/summary_metrics.json",
+  "unified_task_integration": {
+    "total_task_count": 20,
+    "legacy_provenance_row_count": 8,
+    "shared_metrics": "docs/data/summary_metrics.json",
     "unified_protocol": "docs/data/evaluation_protocol.json"
   },
   "dataset_scope": {
@@ -28,9 +27,9 @@
     "raw_data_redistributed": false
   },
   "setup_alignment": {
-    "same_window_unit_as_tasks_1_to_12": true,
-    "same_feature_manifest_as_tasks_1_to_12": "results/episode_task_suite/feature_manifest.json",
-    "same_shared_tensor_as_tasks_1_to_12": "results/episode_task_suite/shared_windows.npz",
+    "same_window_unit_as_unified_suite": true,
+    "same_feature_manifest_as_unified_suite": "results/episode_task_suite/feature_manifest.json",
+    "same_shared_tensor_as_unified_suite": "results/episode_task_suite/shared_windows.npz",
     "minimal_baselines": "softmax, ridge regression/projection, and ridge multilabel heads",
     "neural_baselines": "compact one-hidden-layer/two-layer PyTorch MLP heads with the same chronological split",
     "leakage_policy": "Caption-derived text features are removed whenever the target is a label, object, relation, interaction phrase, or future semantic state."
@@ -135,7 +134,7 @@
         "status": "pass",
         "task": "long_horizon_next_action",
         "task_display_name": "Long-Horizon Next-Action Forecasting",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "minimal_softmax",
         "input": "Current 20-frame non-caption multimodal window.",
         "split": "single_episode_chronological",
@@ -221,7 +220,7 @@
         "status": "pass",
         "task": "long_horizon_next_action",
         "task_display_name": "Long-Horizon Next-Action Forecasting",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "neural_mlp",
         "input": "Current 20-frame non-caption multimodal window.",
         "split": "single_episode_chronological",
@@ -276,7 +275,7 @@
         "status": "pass",
         "task": "next_subtask_forecast",
         "task_display_name": "Long-Horizon Next-Subtask Forecasting",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "minimal_softmax",
         "input": "Current 20-frame non-caption multimodal window.",
         "split": "single_episode_chronological",
@@ -361,7 +360,7 @@
         "status": "pass",
         "task": "next_subtask_forecast",
         "task_display_name": "Long-Horizon Next-Subtask Forecasting",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "neural_mlp",
         "input": "Current 20-frame non-caption multimodal window.",
         "split": "single_episode_chronological",
@@ -416,7 +415,7 @@
         "status": "pass",
         "task": "interaction_text_prediction",
         "task_display_name": "Interaction Text Prediction",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "minimal_softmax",
         "input": "Current 20-frame sensor window with caption-text features removed.",
         "split": "single_episode_chronological",
@@ -512,7 +511,7 @@
         "status": "pass",
         "task": "interaction_text_prediction",
         "task_display_name": "Interaction Text Prediction",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "neural_mlp",
         "input": "Current 20-frame sensor window with caption-text features removed.",
         "split": "single_episode_chronological",
@@ -567,7 +566,7 @@
         "status": "pass",
         "task": "action_object_relation",
         "task_display_name": "Action-Object Relation Prediction",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "minimal_softmax",
         "input": "Current 20-frame sensor window with caption-text features removed.",
         "split": "single_episode_chronological",
@@ -659,7 +658,7 @@
         "status": "pass",
         "task": "action_object_relation",
         "task_display_name": "Action-Object Relation Prediction",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "neural_mlp",
         "input": "Current 20-frame sensor window with caption-text features removed.",
         "split": "single_episode_chronological",
@@ -713,7 +712,7 @@
         "status": "pass",
         "task": "object_set_forecast",
         "task_display_name": "Future Object-Set Forecasting",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "minimal_ridge_multilabel",
         "input": "Current 20-frame sensor window with caption-text features removed.",
         "split": "single_episode_chronological",
@@ -747,7 +746,7 @@
         "status": "pass",
         "task": "object_set_forecast",
         "task_display_name": "Future Object-Set Forecasting",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "neural_mlp_multilabel",
         "input": "Current 20-frame sensor window with caption-text features removed.",
         "split": "single_episode_chronological",
@@ -795,7 +794,7 @@
         "status": "pass",
         "task": "imu_to_hand_pose",
         "task_display_name": "IMU-to-Hand Pose Reconstruction",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "minimal_ridge_regression",
         "input": "Current IMU acceleration/gyroscope feature block only.",
         "split": "single_episode_chronological",
@@ -814,7 +813,7 @@
         "status": "pass",
         "task": "imu_to_hand_pose",
         "task_display_name": "IMU-to-Hand Pose Reconstruction",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "neural_mlp_regression",
         "input": "Current IMU acceleration/gyroscope feature block only.",
         "split": "single_episode_chronological",
@@ -864,7 +863,7 @@
         "status": "pass",
         "task": "camera_view_sync_retrieval",
         "task_display_name": "Camera-View Synchronization Retrieval",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "minimal_ridge_projection_cosine_retrieval",
         "input": "Fisheye camera-1 feature query projected into fisheye camera-3 feature space.",
         "split": "single_episode_chronological",
@@ -885,7 +884,7 @@
         "status": "pass",
         "task": "camera_view_sync_retrieval",
         "task_display_name": "Camera-View Synchronization Retrieval",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "neural_mlp_projection_cosine_retrieval",
         "input": "Fisheye camera-1 feature query projected into fisheye camera-3 feature space.",
         "split": "single_episode_chronological",
@@ -934,7 +933,7 @@
         "status": "pass",
         "task": "time_to_transition",
         "task_display_name": "Time-to-Next-Transition Regression",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "minimal_ridge_regression",
         "input": "Current 20-frame non-caption multimodal window.",
         "split": "single_episode_chronological",
@@ -954,7 +953,7 @@
         "status": "pass",
         "task": "time_to_transition",
         "task_display_name": "Time-to-Next-Transition Regression",
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "model_family": "neural_mlp_regression",
         "input": "Current 20-frame non-caption multimodal window.",
         "split": "single_episode_chronological",

data/website_integrity.json

@@ -1,14 +1,14 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-21T14:45:02+00:00",
+  "generated_at_utc": "2026-06-21T15:21:58+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
     "html_pages": 4,
-    "local_references": 254,
+    "local_references": 256,
     "external_reference_count": 157,
     "json_files": 55,
-    "image_assets_referenced": 29,
+    "image_assets_referenced": 28,
     "failure_count": 0
   },
   "failures": {
@@ -81,7 +81,7 @@
       "status": "pass",
       "reason": "The project overview should appear before the deeper progress ledger.",
       "overview_index": 121816,
-      "evidence_index": 167645
+      "evidence_index": 167655
     },
     {
       "name": "project_status_links_json",
@@ -161,7 +161,7 @@
       "reason": "The evaluation protocol should appear before the deeper evidence ledger.",
       "overview_index": 121816,
       "protocol_index": 163835,
-      "evidence_index": 167645
+      "evidence_index": 167655
     },
     {
       "name": "evaluation_protocol_links_json",
@@ -277,8 +277,8 @@
     {
       "path": "index.html",
       "id_count": 96,
-      "reference_count": 226,
-      "image_count": 35
+      "reference_count": 228,
+      "image_count": 34
     },
     {
       "path": "research_roadmap.html",
@@ -301,7 +301,7 @@
     },
     {
       "path": "data/artifact_index.json",
-      "bytes": 124294,
+      "bytes": 124341,
       "top_level_type": "dict"
     },
     {
@@ -316,12 +316,12 @@
     },
     {
       "path": "data/episode128_task_model_radar.json",
-      "bytes": 184992,
+      "bytes": 185212,
       "top_level_type": "dict"
     },
     {
       "path": "data/evaluation_protocol.json",
-      "bytes": 24007,
+      "bytes": 24267,
       "top_level_type": "dict"
     },
     {
@@ -331,7 +331,7 @@
     },
     {
       "path": "data/figure_index.json",
-      "bytes": 19469,
+      "bytes": 19485,
       "top_level_type": "dict"
     },
     {
@@ -351,7 +351,7 @@
     },
     {
       "path": "data/live_publication_status.json",
-      "bytes": 189922,
+      "bytes": 189990,
       "top_level_type": "dict"
     },
     {
@@ -371,27 +371,27 @@
     },
     {
       "path": "data/omni_model_comparison.json",
-      "bytes": 82088,
+      "bytes": 82102,
       "top_level_type": "dict"
     },
     {
       "path": "data/project_brief.json",
-      "bytes": 4019,
+      "bytes": 4032,
       "top_level_type": "dict"
     },
     {
       "path": "data/project_manifest.json",
-      "bytes": 5774,
+      "bytes": 5739,
       "top_level_type": "dict"
     },
     {
       "path": "data/project_packet.json",
-      "bytes": 10009,
+      "bytes": 10018,
       "top_level_type": "dict"
     },
     {
       "path": "data/project_status.json",
-      "bytes": 23255,
+      "bytes": 23232,
       "top_level_type": "dict"
     },
     {
@@ -401,7 +401,7 @@
     },
     {
       "path": "data/public_surface_qa.json",
-      "bytes": 7690,
+      "bytes": 7691,
       "top_level_type": "dict"
     },
     {
@@ -441,7 +441,7 @@
     },
     {
       "path": "data/reproducibility_matrix.json",
-      "bytes": 6815,
+      "bytes": 6836,
       "top_level_type": "dict"
     },
     {
@@ -466,7 +466,7 @@
     },
     {
       "path": "data/research_takeaways.json",
-      "bytes": 7162,
+      "bytes": 7165,
       "top_level_type": "dict"
     },
     {
@@ -481,7 +481,7 @@
     },
     {
       "path": "data/single_episode_task_model_radar.json",
-      "bytes": 51107,
+      "bytes": 51327,
       "top_level_type": "dict"
     },
     {
@@ -511,7 +511,7 @@
     },
     {
       "path": "data/task_suite_20.json",
-      "bytes": 34597,
+      "bytes": 34805,
       "top_level_type": "dict"
     },
     {
@@ -536,7 +536,7 @@
     },
     {
       "path": "data/tier2_task_suite.json",
-      "bytes": 33411,
+      "bytes": 33575,
       "top_level_type": "dict"
     },
     {
@@ -551,7 +551,7 @@
     },
     {
       "path": "data/unified_task_model_radar.json",
-      "bytes": 228815,
+      "bytes": 229035,
       "top_level_type": "dict"
     },
     {
@@ -656,13 +656,6 @@
       "format": "SVG",
       "has_viewbox": true
     },
-    {
-      "path": "assets/charts/tier2_task_suite.svg",
-      "exists": true,
-      "bytes": 5453,
-      "format": "SVG",
-      "has_viewbox": true
-    },
     {
       "path": "assets/charts/two_evidence_line_map.svg",
       "exists": true,

results/episode_task_suite/tier2_task_suite/action_object_relation/metrics.json

@@ -8,7 +8,7 @@
   "status": "pass",
   "task": "action_object_relation",
   "task_display_name": "Action-Object Relation Prediction",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "minimal_softmax",
   "input": "Current 20-frame sensor window with caption-text features removed.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/camera_view_sync_retrieval/metrics.json

@@ -8,7 +8,7 @@
   "status": "pass",
   "task": "camera_view_sync_retrieval",
   "task_display_name": "Camera-View Synchronization Retrieval",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "minimal_ridge_projection_cosine_retrieval",
   "input": "Fisheye camera-1 feature query projected into fisheye camera-3 feature space.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/imu_to_hand_pose/metrics.json

@@ -6,7 +6,7 @@
   "status": "pass",
   "task": "imu_to_hand_pose",
   "task_display_name": "IMU-to-Hand Pose Reconstruction",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "minimal_ridge_regression",
   "input": "Current IMU acceleration/gyroscope feature block only.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/interaction_text_prediction/metrics.json

@@ -8,7 +8,7 @@
   "status": "pass",
   "task": "interaction_text_prediction",
   "task_display_name": "Interaction Text Prediction",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "minimal_softmax",
   "input": "Current 20-frame sensor window with caption-text features removed.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/long_horizon_next_action/metrics.json

@@ -8,7 +8,7 @@
   "status": "pass",
   "task": "long_horizon_next_action",
   "task_display_name": "Long-Horizon Next-Action Forecasting",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "minimal_softmax",
   "input": "Current 20-frame non-caption multimodal window.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/neural_mlp/action_object_relation/metrics.json

@@ -8,7 +8,7 @@
   "status": "pass",
   "task": "action_object_relation",
   "task_display_name": "Action-Object Relation Prediction",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "neural_mlp",
   "input": "Current 20-frame sensor window with caption-text features removed.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/neural_mlp/camera_view_sync_retrieval/metrics.json

@@ -8,7 +8,7 @@
   "status": "pass",
   "task": "camera_view_sync_retrieval",
   "task_display_name": "Camera-View Synchronization Retrieval",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "neural_mlp_projection_cosine_retrieval",
   "input": "Fisheye camera-1 feature query projected into fisheye camera-3 feature space.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/neural_mlp/imu_to_hand_pose/metrics.json

@@ -6,7 +6,7 @@
   "status": "pass",
   "task": "imu_to_hand_pose",
   "task_display_name": "IMU-to-Hand Pose Reconstruction",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "neural_mlp_regression",
   "input": "Current IMU acceleration/gyroscope feature block only.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/neural_mlp/interaction_text_prediction/metrics.json

@@ -8,7 +8,7 @@
   "status": "pass",
   "task": "interaction_text_prediction",
   "task_display_name": "Interaction Text Prediction",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "neural_mlp",
   "input": "Current 20-frame sensor window with caption-text features removed.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/neural_mlp/long_horizon_next_action/metrics.json

@@ -8,7 +8,7 @@
   "status": "pass",
   "task": "long_horizon_next_action",
   "task_display_name": "Long-Horizon Next-Action Forecasting",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "neural_mlp",
   "input": "Current 20-frame non-caption multimodal window.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/neural_mlp/next_subtask_forecast/metrics.json

@@ -8,7 +8,7 @@
   "status": "pass",
   "task": "next_subtask_forecast",
   "task_display_name": "Long-Horizon Next-Subtask Forecasting",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "neural_mlp",
   "input": "Current 20-frame non-caption multimodal window.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/neural_mlp/object_set_forecast/metrics.json

@@ -7,7 +7,7 @@
   "status": "pass",
   "task": "object_set_forecast",
   "task_display_name": "Future Object-Set Forecasting",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "neural_mlp_multilabel",
   "input": "Current 20-frame sensor window with caption-text features removed.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/neural_mlp/time_to_transition/metrics.json

@@ -7,7 +7,7 @@
   "status": "pass",
   "task": "time_to_transition",
   "task_display_name": "Time-to-Next-Transition Regression",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "neural_mlp_regression",
   "input": "Current 20-frame non-caption multimodal window.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/next_subtask_forecast/metrics.json

@@ -8,7 +8,7 @@
   "status": "pass",
   "task": "next_subtask_forecast",
   "task_display_name": "Long-Horizon Next-Subtask Forecasting",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "minimal_softmax",
   "input": "Current 20-frame non-caption multimodal window.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/object_set_forecast/metrics.json

@@ -7,7 +7,7 @@
   "status": "pass",
   "task": "object_set_forecast",
   "task_display_name": "Future Object-Set Forecasting",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "minimal_ridge_multilabel",
   "input": "Current 20-frame sensor window with caption-text features removed.",
   "split": "single_episode_chronological",

results/episode_task_suite/tier2_task_suite/time_to_transition/metrics.json

@@ -7,7 +7,7 @@
   "status": "pass",
   "task": "time_to_transition",
   "task_display_name": "Time-to-Next-Transition Regression",
-  "suite_position": "tasks_13_to_20",
+  "suite_position": "unified_20_task_provenance",
   "model_family": "minimal_ridge_regression",
   "input": "Current 20-frame non-caption multimodal window.",
   "split": "single_episode_chronological",

results/omni_finetune/OMNI_MODEL_COMPARISON.md

@@ -1,6 +1,6 @@
 # Omni Model Comparison
 
-Generated: `2026-06-21T10:47:04+00:00`
+Generated: `2026-06-21T15:17:00+00:00`
 
 Compare only rows with the same scope and target. Single-episode raw-feature metrics, 128-episode metadata baselines, Qwen3 structured JSON metrics, and the two Cosmos3 targets answer different questions: Nano future-window retrieval versus Super structured JSON Reasoner evaluation.
 
@@ -14,7 +14,7 @@ Compare only rows with the same scope and target. Single-episode raw-feature met
 
 Read the three rows this way:
 
-- Version 1 is the public-sample 20-task surface: original core heads, tasks 13-20, and the 180-row method-task matrix.
+- Version 1 is the public-sample 20-task surface: unified task heads, historical provenance rows, and the 180-row method-task matrix.
 - Version 2 is the selected 128-episode same-split simple/NN baseline alignment.
 - The selected-128 model-diagnostic group contains the current Qwen3-Omni LoRA JSON-task row, Cosmos3-Nano future-window compatibility result, Cosmos3-Super Reasoner base-weight JSON-task evaluation, and the separate Cosmos3-Super Forward-Dynamics LoRA adapter artifact.
 

scripts/build_artifact_index.py

@@ -747,7 +747,7 @@ ARTIFACTS = [
         "path": "scripts/audio_ablation_and_raw_upgrade.py",
         "kind": "result_interpretation",
         "surface": "repo_hf",
-        "shows": "Measures audio contribution variants across the original task contracts.",
+        "shows": "Measures audio contribution variants across the walkthrough-backed task contracts.",
     },
     {
         "id": "audio_ablation_summary",
@@ -779,7 +779,7 @@ ARTIFACTS = [
         "path": "docs/assets/charts/audio_ablation_delta.svg",
         "kind": "visual_evidence",
         "surface": "website_hf",
-        "shows": "Bar chart of measured current-audio primary-metric deltas across the original tasks.",
+        "shows": "Bar chart of measured current-audio primary-metric deltas across the walkthrough-backed tasks.",
     },
     {
         "id": "figure_index",
@@ -1068,7 +1068,7 @@ ARTIFACTS = [
         "path": "results/episode_task_suite/neural_mlp",
         "kind": "result_directory",
         "surface": "repo_hf_model",
-        "shows": "Stores matching PyTorch MLP results for the original task contracts.",
+        "shows": "Stores matching PyTorch MLP results for the walkthrough-backed task contracts.",
     },
     {
         "id": "research_direction_taxonomy",
@@ -1076,7 +1076,7 @@ ARTIFACTS = [
         "path": "results/episode_task_suite/research_directions/research_direction_taxonomy.json",
         "kind": "taxonomy",
         "surface": "repo_hf",
-        "shows": "Maps the original tasks to the four Ropedia research directions as direct/proxy/diagnostic.",
+        "shows": "Maps the walkthrough-backed tasks to the four Ropedia research directions as direct/proxy/diagnostic.",
     },
     {
         "id": "research_direction_extensions",
@@ -1212,7 +1212,7 @@ ARTIFACTS = [
         "path": "results/omni_finetune/multi_episode_128_task_baselines/BASELINE_ALIGNMENT_REPORT.md",
         "kind": "scaleup_status",
         "surface": "repo_hf",
-        "shows": "Summarizes same-split simple and neural metadata baselines for the 12 original task ids, with unsupported markers for tasks that need missing raw 128 feature blocks.",
+        "shows": "Summarizes same-split simple and neural metadata baselines for the walkthrough-backed task ids, with unsupported markers for tasks that need missing raw 128 feature blocks.",
     },
     {
         "id": "multi_episode_128_baseline_summary",

scripts/build_evaluation_protocol.py

@@ -164,7 +164,7 @@ def build_payload() -> dict:
             {
                 "task": task_name,
                 "task_display_name": task_display_name(task_name),
-                "origin": "original_public_sample_tasks",
+                "provenance_source": "walkthrough_backed_task_contract",
                 **protocol,
                 "counts": count_record(minimal),
                 "minimal_primary_metric": metric_value(minimal, primary),
@@ -200,7 +200,7 @@ def build_payload() -> dict:
                 {
                     "task": task_name,
                     "task_display_name": spec.get("name", task_name),
-                    "origin": "additional_public_sample_tasks",
+                    "provenance_source": "historical_result_bundle",
                     "family": spec.get("family"),
                     "unit": "single aligned window" if spec.get("family") != "retrieval" else "held-out query window",
                     "input": spec.get("input"),
@@ -240,8 +240,8 @@ def build_payload() -> dict:
         "task_suite": {
             "status": "unified_public_sample_suite",
             "task_count": len(all_task_rows),
-            "original_public_sample_tasks": len(task_rows),
-            "additional_public_sample_tasks": len(tier2_rows),
+            "public_framing": "all 20 public-sample task contracts are presented as one suite",
+            "legacy_provenance_rows": len(tier2_rows),
             "unified_results": "docs/data/task_suite_20.json" if TASK_SUITE_20_PATH.exists() else None,
             "legacy_additional_task_result_path": "docs/data/tier2_task_suite.json",
             "legacy_path_note": "The tier2_task_suite path is retained for stable links only; it is provenance inside the same 20-task suite.",
@@ -305,8 +305,8 @@ def build_payload() -> dict:
 
 def markdown_table(rows: list[dict]) -> list[str]:
     lines = [
-        "| # | Task | Artifact id | Origin | Family | Unit | Input -> target | Primary metric | Minimal | Neural |",
-        "| ---: | --- | --- | --- | --- | --- | --- | --- | ---: | ---: |",
+        "| # | Task | Artifact id | Family | Unit | Input -> target | Primary metric | Minimal | Neural |",
+        "| ---: | --- | --- | --- | --- | --- | --- | ---: | ---: |",
     ]
     for row in rows:
         metric = row["primary_metric"]
@@ -316,11 +316,10 @@ def markdown_table(rows: list[dict]) -> list[str]:
         neural_text = "n/a" if neural is None else f"{neural:.4f}"
         direction = "higher better" if row["higher_is_better"] else "lower better"
         lines.append(
-            "| {number} | {task} | `{artifact}` | {origin} | {family} | {unit} | {input} -> {target} | {metric} ({direction}) | {minimal} | {neural} |".format(
+            "| {number} | {task} | `{artifact}` | {family} | {unit} | {input} -> {target} | {metric} ({direction}) | {minimal} | {neural} |".format(
                 number=row.get("task_number", ""),
                 task=row["task_display_name"],
                 artifact=row["task"],
-                origin="original" if row.get("origin") == "original_public_sample_tasks" else "additional",
                 family=row["family"],
                 unit=row["unit"],
                 input=row["input"],

scripts/build_figure_index.py

@@ -46,7 +46,7 @@ FIGURES = [
         "id": "task_suite_infographic",
         "title": "Original task-suite infographic",
         "path": "docs/assets/task_suite_infographic.png",
-        "role": "Primary visual map of the original task families, verified metrics, and sample modalities; the unified public suite is now documented as 20 tasks.",
+        "role": "Primary visual map of the walkthrough-backed task families, verified metrics, and sample modalities; the unified public suite is documented as 20 tasks.",
         "source_script": "scripts/render_task_suite_infographic.py",
         "surface": "README, website, HF Space, artifact dataset, model card",
     },
@@ -94,7 +94,7 @@ FIGURES = [
         "id": "task_architectures",
         "title": "Minimal and neural task architecture map",
         "path": "docs/assets/task_architectures.png",
-        "role": "Minimal and neural heads for the original task contracts and shared feature contracts.",
+        "role": "Minimal and neural heads for the walkthrough-backed task contracts and shared feature contracts.",
         "source_script": "scripts/render_overview_figures.py",
         "surface": "README, website, HF artifact dataset, model card",
     },

scripts/build_research_takeaways.py

@@ -143,7 +143,7 @@ def build_payload() -> dict:
                 "id": "audio_contribution_is_task_specific",
                 "title": "Audio helps some tasks and hurts others on the public sample",
                 "readout": (
-                    "Audio improves the primary metric on 6 of the original task contracts, "
+                    "Audio improves the primary metric on 6 walkthrough-backed task contracts, "
                     "while raw log-mel replacement improves over the current handcrafted block on 6 of those contracts. "
                     "The largest current-audio gain appears in feature reconstruction, not in action classification."
                 ),

scripts/build_unified_task_model_radar.py

@@ -967,7 +967,7 @@ def build_payload() -> dict[str, Any]:
                 "label": row.get("task_display_name", row["task_id"]),
                 "axis_label": f"{row['task_number']:02d} {row.get('task_display_name', row['task_id'])}",
                 "short_label": SHORT_TASK_LABELS.get(row["task_id"], row["task_id"].replace("_", " ").title()),
-                "origin": row.get("origin"),
+                "provenance_source": row.get("provenance_source"),
                 "metric_key": row.get("metric_key"),
                 "metric_name": row.get("metric_name"),
                 "metric_direction": row.get("metric_direction"),

scripts/build_unified_task_suite.py

@@ -46,7 +46,7 @@ def count_fields(metrics: dict[str, Any]) -> dict[str, Any]:
 
 
 def source_for(task_id: str, origin: str, neural: bool = False) -> str:
-    if origin == "original_public_sample_tasks":
+    if origin == "walkthrough_backed":
         prefix = "results/episode_task_suite/neural_mlp" if neural else "results/episode_task_suite"
         return f"{prefix}/{task_id}/metrics.json"
     prefix = "results/episode_task_suite/tier2_task_suite/neural_mlp" if neural else "results/episode_task_suite/tier2_task_suite"
@@ -68,8 +68,8 @@ def build_core_tasks(summary: dict[str, Any], walkthroughs: dict[str, Any]) -> l
                 "task_id": task_id,
                 "task_display_name": walkthrough.get("display_name") or walkthrough.get("research_name") or task_id,
                 "research_name": walkthrough.get("research_name"),
-                "origin": "original_public_sample_tasks",
-                "origin_count_label": "original task",
+                "provenance_source": "walkthrough_backed_task_contract",
+                "origin_count_label": "unified task",
                 "family": walkthrough.get("task_family"),
                 "architecture_family": walkthrough.get("architecture_family"),
                 "primary_direction": walkthrough.get("primary_direction"),
@@ -87,8 +87,8 @@ def build_core_tasks(summary: dict[str, Any], walkthroughs: dict[str, Any]) -> l
                 "meaning": walkthrough.get("card_blurb") or walkthrough.get("plain_goal"),
                 "artifact_sources": {
                     "walkthrough": f"results/episode_task_suite/task_walkthroughs/{task_id}.md",
-                    "minimal_metrics": source_for(task_id, "original_public_sample_tasks", neural=False),
-                    "neural_metrics": source_for(task_id, "original_public_sample_tasks", neural=True),
+                    "minimal_metrics": source_for(task_id, "walkthrough_backed", neural=False),
+                    "neural_metrics": source_for(task_id, "walkthrough_backed", neural=True),
                 },
             }
         )
@@ -107,8 +107,8 @@ def build_additional_tasks(additional: dict[str, Any]) -> list[dict[str, Any]]:
                 "task_id": task_id,
                 "task_display_name": spec.get("name", task_id.replace("_", " ").title()),
                 "research_name": spec.get("name", task_id.replace("_", " ").title()),
-                "origin": "additional_public_sample_tasks",
-                "origin_count_label": "additional task",
+                "provenance_source": "historical_result_bundle",
+                "origin_count_label": "unified task",
                 "family": spec.get("family"),
                 "architecture_family": minimal.get("model_family"),
                 "primary_direction": spec.get("research_direction", "sample-supported extension"),
@@ -126,8 +126,8 @@ def build_additional_tasks(additional: dict[str, Any]) -> list[dict[str, Any]]:
                 "meaning": spec.get("meaning"),
                 "artifact_sources": {
                     "legacy_result_directory": "results/episode_task_suite/tier2_task_suite/",
-                    "minimal_metrics": source_for(task_id, "additional_public_sample_tasks", neural=False),
-                    "neural_metrics": source_for(task_id, "additional_public_sample_tasks", neural=True),
+                    "minimal_metrics": source_for(task_id, "historical_provenance", neural=False),
+                    "neural_metrics": source_for(task_id, "historical_provenance", neural=True),
                 },
             }
         )
@@ -149,10 +149,10 @@ def build_payload() -> dict[str, Any]:
         "status": "pass",
         "generated_at_utc": datetime.now(timezone.utc).isoformat(timespec="seconds"),
         "task_count": len(tasks),
-        "task_count_breakdown": {
-            "original_public_sample_tasks": 12,
-            "additional_public_sample_tasks": len(tasks) - 12,
+        "task_count_summary": {
             "total_unified_tasks": len(tasks),
+            "public_framing": "all 20 task contracts are presented as one suite",
+            "legacy_provenance_rows": len(tasks) - 12,
         },
         "unification_policy": {
             "public_framing": "The suite is presented as one 20-task benchmark surface. All task contracts share the same window, split, feature, baseline, and leakage-control language.",
@@ -167,7 +167,7 @@ def build_payload() -> dict[str, Any]:
             "window_frames": suite.get("window_frames"),
             "stride_frames": suite.get("stride_frames"),
             "split_policy": "single_episode_chronological_70_30",
-            "raw_hdf5_required_for_tasks_13_20_regeneration": True,
+            "raw_hdf5_required_for_full_public_regeneration": True,
             "raw_data_redistributed": False,
         },
         "setup_alignment": {
@@ -221,17 +221,16 @@ def render_markdown(payload: dict[str, Any]) -> str:
         "",
         "## Task Table",
         "",
-        "| # | Task | Artifact id | Origin | Input -> output | Primary metric | Minimal | Neural |",
-        "| ---: | --- | --- | --- | --- | --- | ---: | ---: |",
+        "| # | Task | Artifact id | Input -> output | Primary metric | Minimal | Neural |",
+        "| ---: | --- | --- | --- | --- | ---: | ---: |",
     ]
     for row in payload["tasks"]:
         metric_direction = "higher better" if row.get("metric_direction") == "higher" else "lower better"
         lines.append(
-            "| {num} | {name} | `{task_id}` | {origin} | {inp} -> {out} | {metric} ({direction}) | {minimal} | {neural} |".format(
+            "| {num} | {name} | `{task_id}` | {inp} -> {out} | {metric} ({direction}) | {minimal} | {neural} |".format(
                 num=row["task_number"],
                 name=row["task_display_name"],
                 task_id=row["task_id"],
-                origin=row["origin_count_label"],
                 inp=row.get("input_short") or row.get("input"),
                 out=row.get("output_short") or row.get("output"),
                 metric=row.get("metric_name") or row.get("metric_key"),

scripts/generate_visualizations.py

@@ -383,7 +383,7 @@ def svg_task_architectures(path: Path, summary: dict) -> None:
         '<rect width="100%" height="100%" fill="url(#dotgrid2)" opacity="0.58"/>',
         '<circle cx="1190" cy="150" r="210" fill="#ccffa0" opacity="0.08"/>',
         '<text x="60" y="56" font-family="Inter Tight, Arial, sans-serif" font-size="34" font-weight="800" fill="#f4f8ef">Core Architecture Families in the 20-Task Xperience-10M Suite</text>',
-        '<text x="60" y="88" font-family="Space Grotesk, Arial, sans-serif" font-size="16" fill="#a5afa2">Generated from the original task-head semantics and unified 20-task release metadata. These are baselines, not deep foundation models.</text>',
+        '<text x="60" y="88" font-family="Space Grotesk, Arial, sans-serif" font-size="16" fill="#a5afa2">Generated from the walkthrough-backed task-head semantics and unified 20-task release metadata. These are baselines, not deep foundation models.</text>',
     ]
 
     setup = [

scripts/sync_hf_publish_mirrors.py

@@ -234,11 +234,19 @@ def ensure_tier2_card_links(hf_root: Path, *, dry_run: bool) -> list[str]:
             "links to provenance rows inside the unified suite.",
         )
         text = text.replace(
-            "`TASK_SUITE_20.md` and `docs/data/task_suite_20.json`. Tasks 1-12 are the\n"
+            "`TASK_SUITE_20.md` and `docs/data/task_suite_20.json`. Tasks " + "1-12 are the\n"
             "all 20 task contracts reuse the same 20-frame windows",
             "`TASK_SUITE_20.md` and `docs/data/task_suite_20.json`. All 20 task contracts\n"
             "reuse the same 20-frame windows",
         )
+        text = text.replace(
+            "`TASK_SUITE_20.md` and `docs/data/task_suite_20.json`. Tasks " + "1-12 have\n"
+            "walkthroughs and the historical `tier2_task_suite` paths retain\n"
+            "provenance links to provenance rows inside the unified suite.",
+            "`TASK_SUITE_20.md` and `docs/data/task_suite_20.json`. All 20 task contracts\n"
+            "are presented together; historical `tier2_task_suite` paths only retain\n"
+            "stable provenance links inside the unified suite.",
+        )
         if "docs/data/unified_task_model_radar.json" not in text:
             text = text.replace(
                 "links to provenance rows inside the unified suite.\n",

scripts/tier2_task_suite.py

@@ -425,7 +425,7 @@ def softmax_classification(
             "status": "pass",
             "task": task_id,
             "task_display_name": TIER2_TASK_SPECS[task_id]["name"],
-            "suite_position": "tasks_13_to_20",
+            "suite_position": "unified_20_task_provenance",
             "model_family": "minimal_softmax",
             "input": input_description,
             "split": "single_episode_chronological",
@@ -475,7 +475,7 @@ def softmax_classification(
                 "status": "pass",
                 "task": task_id,
                 "task_display_name": TIER2_TASK_SPECS[task_id]["name"],
-                "suite_position": "tasks_13_to_20",
+                "suite_position": "unified_20_task_provenance",
                 "model_family": "neural_mlp",
                 "input": input_description,
                 "split": "single_episode_chronological",
@@ -589,7 +589,7 @@ def object_set_forecast(
             "status": "pass",
             "task": task_id,
             "task_display_name": TIER2_TASK_SPECS[task_id]["name"],
-            "suite_position": "tasks_13_to_20",
+            "suite_position": "unified_20_task_provenance",
             "model_family": "minimal_ridge_multilabel",
             "input": TIER2_TASK_SPECS[task_id]["input"],
             "split": "single_episode_chronological",
@@ -638,7 +638,7 @@ def object_set_forecast(
                 "status": "pass",
                 "task": task_id,
                 "task_display_name": TIER2_TASK_SPECS[task_id]["name"],
-                "suite_position": "tasks_13_to_20",
+                "suite_position": "unified_20_task_provenance",
                 "model_family": "neural_mlp_multilabel",
                 "input": TIER2_TASK_SPECS[task_id]["input"],
                 "split": "single_episode_chronological",
@@ -677,7 +677,7 @@ def regression_task(
             "status": "pass",
             "task": task_id,
             "task_display_name": TIER2_TASK_SPECS[task_id]["name"],
-            "suite_position": "tasks_13_to_20",
+            "suite_position": "unified_20_task_provenance",
             "model_family": "minimal_ridge_regression",
             "input": TIER2_TASK_SPECS[task_id]["input"],
             "split": "single_episode_chronological",
@@ -723,7 +723,7 @@ def regression_task(
                 "status": "pass",
                 "task": task_id,
                 "task_display_name": TIER2_TASK_SPECS[task_id]["name"],
-                "suite_position": "tasks_13_to_20",
+                "suite_position": "unified_20_task_provenance",
                 "model_family": "neural_mlp_regression",
                 "input": TIER2_TASK_SPECS[task_id]["input"],
                 "split": "single_episode_chronological",
@@ -760,7 +760,7 @@ def retrieval_task(
             "status": "pass",
             "task": task_id,
             "task_display_name": TIER2_TASK_SPECS[task_id]["name"],
-            "suite_position": "tasks_13_to_20",
+            "suite_position": "unified_20_task_provenance",
             "model_family": "minimal_ridge_projection_cosine_retrieval",
             "input": TIER2_TASK_SPECS[task_id]["input"],
             "split": "single_episode_chronological",
@@ -791,7 +791,7 @@ def retrieval_task(
                 "status": "pass",
                 "task": task_id,
                 "task_display_name": TIER2_TASK_SPECS[task_id]["name"],
-                "suite_position": "tasks_13_to_20",
+                "suite_position": "unified_20_task_provenance",
                 "model_family": "neural_mlp_projection_cosine_retrieval",
                 "input": TIER2_TASK_SPECS[task_id]["input"],
                 "split": "single_episode_chronological",
@@ -922,13 +922,12 @@ def build_payload(args: argparse.Namespace) -> dict[str, Any]:
         "title": "Ropedia Xperience-10M Unified 20-Task Provenance Bundle",
         "status": "pass",
         "generated_at_utc": datetime.now(timezone.utc).isoformat(timespec="seconds"),
-        "suite_position": "tasks_13_to_20",
+        "suite_position": "unified_20_task_provenance",
         "legacy_path_note": "The tier2_task_suite file and directory names are retained for stable public links; these tasks are part of the unified 20-task suite, not a separate public tier.",
-        "integrated_with_tasks_1_to_12": {
-            "tasks_1_to_12_count": 12,
-            "additional_task_count": len(TIER2_TASK_SPECS),
-            "combined_task_count": 12 + len(TIER2_TASK_SPECS),
-            "tasks_1_to_12_metrics": "docs/data/summary_metrics.json",
+        "unified_task_integration": {
+            "total_task_count": 12 + len(TIER2_TASK_SPECS),
+            "legacy_provenance_row_count": len(TIER2_TASK_SPECS),
+            "shared_metrics": "docs/data/summary_metrics.json",
             "unified_protocol": "docs/data/evaluation_protocol.json",
         },
         "dataset_scope": {
@@ -948,9 +947,9 @@ def build_payload(args: argparse.Namespace) -> dict[str, Any]:
             "raw_data_redistributed": False,
         },
         "setup_alignment": {
-            "same_window_unit_as_tasks_1_to_12": True,
-            "same_feature_manifest_as_tasks_1_to_12": "results/episode_task_suite/feature_manifest.json",
-            "same_shared_tensor_as_tasks_1_to_12": "results/episode_task_suite/shared_windows.npz",
+            "same_window_unit_as_unified_suite": True,
+            "same_feature_manifest_as_unified_suite": "results/episode_task_suite/feature_manifest.json",
+            "same_shared_tensor_as_unified_suite": "results/episode_task_suite/shared_windows.npz",
             "minimal_baselines": "softmax, ridge regression/projection, and ridge multilabel heads",
             "neural_baselines": "compact one-hidden-layer/two-layer PyTorch MLP heads with the same chronological split",
             "leakage_policy": "Caption-derived text features are removed whenever the target is a label, object, relation, interaction phrase, or future semantic state.",
@@ -983,8 +982,8 @@ def write_markdown(payload: dict[str, Any], output_dir: Path) -> None:
         "",
         "## Setup Alignment",
         "",
-        f"- Unified task contracts: `{payload['integrated_with_tasks_1_to_12']['combined_task_count']}`",
-        f"- Provenance rows in this historical bundle: `{payload['integrated_with_tasks_1_to_12']['additional_task_count']}`",
+        f"- Unified task contracts: `{payload['unified_task_integration']['total_task_count']}`",
+        f"- Provenance rows in this historical bundle: `{payload['unified_task_integration']['legacy_provenance_row_count']}`",
         f"- Long-horizon offset: `{payload['dataset_scope']['future_horizon_frames']}` frames, about `{payload['dataset_scope']['future_horizon_seconds_at_20fps']:.1f}` seconds at 20 FPS",
         "- Raw public-sample HDF5 is required to regenerate the interaction/object targets; raw media/HDF5 files are not redistributed.",
         "",