{
  "key": "d5-s23-cancel-phat-band",
  "idea": "Apply exactly-one-tick retreat cancellation only inside a middle-phat band, spreads 2 and 3.",
  "approach": "Gate the existing RC cancel wrapper on its current adjusted phat, with inclusive 5-95c, 10-90c, and 20-80c bands. Expose phat with one assignment; append a subclass providing the band predicate. Outside the band return the underlying pre-cancel actions. Select by target-spread paired tuning mean, freeze, then screen once on holdout.",
  "tried": [
    {
      "name": "band05_95",
      "code_sha256": "a93157ffe44e3d2b4e7f8f7c2b4e7ed2a7874642b2c1e86682fa049e7d73500e",
      "mean_diff": -0.6606125637018871,
      "se": 0.22170914737045072,
      "n": 106,
      "score_scope": "target spreads 2 and 3",
      "overall_mean_diff": -0.35012465876200016,
      "overall_se": 0.11955071290389561
    },
    {
      "name": "band10_90",
      "code_sha256": "d28553aee096c7c7e9586abe4417e8dd54d71f3e8bf5a0c478a6dc2a2153659c",
      "mean_diff": -0.9204853724575468,
      "se": 0.2868638797608492,
      "n": 106,
      "score_scope": "target spreads 2 and 3",
      "overall_mean_diff": -0.4878572474024998,
      "overall_se": 0.15515511034471866
    },
    {
      "name": "band20_80",
      "code_sha256": "6d53d73436b81035a588f045521f15482da7ebed2fda88f0c0d05d589eba6914",
      "mean_diff": -0.8338982340452822,
      "se": 0.3912045644391305,
      "n": 106,
      "score_scope": "target spreads 2 and 3",
      "overall_mean_diff": -0.4419660640439996,
      "overall_se": 0.208969149630276
    }
  ],
  "next": "Screen only; no promotion. Retain RC: the selected band has no positive holdout evidence.",
  "code": "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",
  "code_sha256": "a93157ffe44e3d2b4e7f8f7c2b4e7ed2a7874642b2c1e86682fa049e7d73500e",
  "comparator_sha256": "3c07bdcd221ac25729c3ebc92b21ac9e2014510ecb85816c4391ed81e933291f",
  "target_spreads": [
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  "tuning": {
    "seeds": {
      "start": 330000,
      "end": 330199,
      "n": 200
    },
    "selected": "band05_95",
    "selection_rule": "Highest paired mean on target spreads 2 and 3 across all 200 tuning seeds; inclusive probability bands.",
    "frozen_before_holdout": true,
    "variants": {
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        "by_spread": {
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      "band10_90": {
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        "overall": {
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        "by_spread": {
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          "4": {
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      },
      "band20_80": {
        "code_sha256": "6d53d73436b81035a588f045521f15482da7ebed2fda88f0c0d05d589eba6914",
        "target": {
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        "overall": {
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  "failures": [],
  "check_values": {
    "310000": 17.5126554022,
    "310001": 20.6298693268,
    "310002": 2.3903113616,
    "310003": 248.006347259
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  "validation": {
    "simulator_commit": "b244530ee2a6247b5f930830eeca9dd950da0e7e",
    "simulator_unmodified": true,
    "default_config": true,
    "default_parameter_variance": true,
    "steps": 2000,
    "single_process": true,
    "sandbox": false,
    "chunk_max_seeds": 50,
    "unique_seed_strategy_records": true,
    "off_target_exact_zero": true,
    "finalist_seeds_used": false,
    "structural_tests": "Inclusive band endpoints; bid and ask one-tick retreats; placement suppression; cancellation deduplication; probe clearing; outside-band action and bookkeeping preservation.",
    "interpretation": "The brief names RC, whose existing wrapper already cancels on every eligible retreat. To test the requested gating change, outside-band actions mean RC core actions before that wrapper, so its retreat cancellation is disabled there. All other RC logic is unchanged."
  },
  "code_encoding": "gzip+base64"
}