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Datasets:
osazuwa
/
wrong-move-reference-v1

Tags:
causal-inference
world-models
reinforcement-learning
Synthetic
match-3
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wrong-move-reference-v1
File size: 3,351 Bytes
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{
  "schema_version": 1,
  "name": "wrong-move-reference-v1",
  "status": "accepted_reference_benchmark",
  "accepted_on": "2026-09-11",
  "acceptance": {
    "retrospective": true,
    "retuned_after_validation": false,
    "primary_result": "15 of 15 held-out cells reproduce recommendation reversal and positive causal regret",
    "conservative_audit": "13 of 15 held-out cells pass the complete auxiliary audit"
  },
  "source": {
    "simulator_revision": "0c56017ac3a1cad42d551e35cc790bb7c8393a24",
    "frozen_candidate_sha256": "37fc819c5a859ad472fd15016b34fdaed6484e7b55375c9af942b9f41eb99f40",
    "validation_report_sha256": "488d328ec10206caddca04f704c47aa045f2689b2b1e0991b59997df26873c51",
    "quota_calibration_file": "accepted_calibration.json",
    "quota_calibration_sha256": "5be88991f51593476fe49ac69089b4753040135e566f738b13d3f5254e27a361",
    "win_propensity_sha256": "c6d7308590d1327633e9ef2e8caa74a0e462439646182c49a99470730bd54dea",
    "mechanics_sha256": {
      "board.py": "96bc976d832f8b27ba53ef46bfc8c9f7c02a95606036a1ebd3914b37a5c5071e",
      "causal_queries.py": "c27131d3a6efdaef7fb7f59227dcab599a53323b33f5e51762fcfbe2052f45d7",
      "policy.py": "e47ffb2b8ac2782b1ab0e7efca210832513ccfad7f5518cc812605f78b4aeb09",
      "retention.py": "f16f490b41677390addd688312951572c6b327e72e27e612b9cd77b737af3155",
      "scm.py": "9a7435148a010769874b114459120d3631740822cb228ab96b5634f080ddce6e",
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    }
  },
  "candidate": {
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    "experience_target": 0.164262759633189,
    "experience_update_rate": 0.553511867172367,
    "levels": {
      "orchard": {
        "intercept": -11.95228973603845,
        "experience_curvature_easy": 0.7399082077039942,
        "experience_curvature_overchallenge": 1.2847704867520313,
        "margin_curvature_easy": 35.98993720552555,
        "margin_curvature_overchallenge": 66.34498111523541,
        "margin_target": -0.13473217976862334
      },
      "harbour": {
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        "experience_curvature_easy": 0.17810063157841124,
        "experience_curvature_overchallenge": 0.30080257488180845,
        "margin_curvature_easy": 28.544031059020828,
        "margin_curvature_overchallenge": 45.90075543126402,
        "margin_target": -0.06850300398162373
      },
      "foundry": {
        "intercept": -9.299316921462278,
        "experience_curvature_easy": 0.2755883650795542,
        "experience_curvature_overchallenge": 1.1211178618583253,
        "margin_curvature_easy": 33.911232087601945,
        "margin_curvature_overchallenge": 73.16899131014536,
        "margin_target": -0.1644139861290589
      }
    }
  },
  "regimes": {
    "natural": {
      "skill_gains": [1.9, 2.0, 1.8],
      "sigmas": [0.8, 0.8, 0.8]
    },
    "randomized": {
      "skill_gains": [0.0, 0.0, 0.0],
      "sigmas": [2.0615528128088303, 2.1540659228538015, 1.969771560359221],
      "matching": "Preserves natural marginal assignment variance conditional on level and baseline tier"
    }
  },
  "dataset": {
    "seed": 12011,
    "split_seed": 12017,
    "players": 2400,
    "max_attempts": 20,
    "shard_size": 240,
    "split_fractions": {
      "train": 0.7,
      "validation": 0.15,
      "test": 0.15
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  }
}