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      "first_divergence": null
    },
    "note": "Ordinary LM-head gate recorded separately; letter readout acceptance uses the two transcripts above."
  },
  "measured_through_coreai_kit": {
    "schema": "coreai-kit-supervisor-measurements/1",
    "provenance": "Supervisor supplied in rounds/02.instruction.md; measured through coreai-kit, not rerun in this conversion round",
    "supplied_text": "Facts the supervisor measured on the kit side (2026-09-23 05:2x–05:4x JST, worktree ~/code/coreai-kit-models-wt,\n`Decision.Format.sharedState`, the sequential engine, the kit's own chat-template rendering) — quote as \"measured\nthrough coreai-kit\", do not re-derive:\n- `decide-cli parity` on results/fixtures.json: the 40 `choice` and `noul` rows — tokens identical 40/40 (the kit's\n  chat-template rendering equals the author's `compile()` byte for byte), label slots 40/40, option argmax 40/40,\n  max |Δp| 0.0055, mean 0.0002. The 8 `score_level` rows are skipped: the kit's question kinds have no primitive of\n  that name (the author's score_level is a yes/no on one proposition, the kit's `noul`, but the JSON says\n  `\"primitive\": \"score_level\"` and the kit renders `\"noul\"`). Median 2.8 s per fixture question over those 40 rows\n  (124–1,672 compiled tokens, S=1 prefill), 24 s for the 1,672-token row.\n- A two-question workflow request (a 20-token state, a 3-criteria choice and a noul): 2,069 ms for the 134-token\n  row and 1,540 ms for the 107-token row, 0 tokens reused (the recurrent hybrid re-prefills every row) — about\n  15 ms per token on the sequential engine. Answers: close 0.999; refund asked P(yes) 0.000.\n- SemIf's authored144 (144 English rows, 3 options each, SemIf's gold labels, its unchanged `benchmarks/evaluate.py`),\n  the kit's own rendering of each row as a `choice`: raw 131/144, **mean family balanced accuracy 0.906**, median\n  1.96 s per decision. For scale on the same rows and evaluator the kit README reports Qwen3.5-4B int8 zero-shot\n  0.821 and MiniCPM5-2B int8 0.681, and the OpenThai run 0.725. Numbers, not a ranking.\n- The kit's own \"which model\" mistake, for the knowledge page's Swift paragraph: an earlier `ask` measurement of\n  the OpenThai sibling had silently used the catalog default model because the command ignored `--bundle`; the\n  command was fixed and every figure above was taken with the model line printed (`model: apus_openjev_… format: sharedState`).\n",
    "measurement_date": "2026-09-23 JST",
    "worktree_read_only": "~/code/coreai-kit-models-wt",
    "format": "Decision.Format.sharedState",
    "engine": "coreai-sequential",
    "chat_rendering": "kit own chat template; thinking closed",
    "parity": {
      "rows": 40,
      "token_identical": 40,
      "label_slots": 40,
      "option_argmax": 40,
      "max_abs_probability_error": 0.0055,
      "mean_error": 0.0002,
      "skipped_score_level_rows": 8,
      "skip_reason": "Kit has no score_level question kind; although semantically a yes/no proposition, rendering noul changes primitive JSON and the prompt.",
      "median_seconds_per_question": 2.8,
      "compiled_tokens_min": 124,
      "compiled_tokens_max": 1672,
      "wide_row_tokens": 1672,
      "wide_row_seconds": 24
    },
    "workflow": {
      "state_tokens": 20,
      "questions": [
        {
          "primitive": "choice",
          "criteria": 3,
          "tokens": 134,
          "milliseconds": 2069,
          "answer": "close",
          "probability": 0.999
        },
        {
          "primitive": "noul",
          "tokens": 107,
          "milliseconds": 1540,
          "proposition": "refund asked",
          "yes_probability": 0.0
        }
      ],
      "reused_tokens": 0,
      "approx_sequential_milliseconds_per_token": 15
    },
    "semif": {
      "dataset": "SemIf authored144",
      "rows": 144,
      "language": "en",
      "options_per_row": 3,
      "labels": "SemIf gold",
      "evaluator": "unchanged benchmarks/evaluate.py",
      "rendered_primitive": "choice",
      "raw_correct": 131,
      "mean_family_balanced_accuracy": 0.906,
      "median_seconds_per_decision": 1.96,
      "same_rows_and_evaluator_context": {
        "Qwen3.5-4B int8 zero-shot": 0.821,
        "MiniCPM5-2B int8": 0.681,
        "OpenThai run": 0.725
      },
      "comparison_note": "Numbers for scale, not a ranking."
    },
    "model_selection_trap": "An earlier OpenThai ask measurement ignored --bundle and used the catalog default; the command was fixed, and all supplied measurements printed model: apus_openjev_… format: sharedState."
  },
  "through_coreai_kit": {
    "tokens_equal": 40,
    "slots_equal": 40,
    "option_argmax_equal": 40,
    "max_abs_dp": 0.0055,
    "mean_abs_dp": 0.0002,
    "skipped_score_level_rows": 8,
    "record": "models/apus-openjev-v1-4b/measurements-coreai-kit.json",
    "provenance": "measured through coreai-kit; supervisor-provided, not re-derived"
  },
  "fixture": "models/apus-openjev-v1-4b/fixtures-apus-openjev-v1-4b.json",
  "generated_from": "the two executed letter transcripts' summary blocks; shape follows d6ca61a:models/openthai-systemone/gate-openthai-systemone.json",
  "benchmark": "llm-benchmark.json",
  "scope": "Mac GPU full-depth path; no low-effort graph, phone gate, upload, or registry mutation."
}