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  "seconds_per_simulation": 0.5956554490153212,
  "notes": [
    "Unmodified danrobinson/prediction-market-challenge simulator at commit b244530ee2a6247b5f930830eeca9dd950da0e7e; Python 3.13.5; standard-library dependencies only.",
    "For every seed s, cfg = runner.sample_config(ChallengeConfig(), ParameterVariance(), seed=s). Run BASE then CANDIDATE using SimulationEngine(cfg, loader.load_strategy_factory(path), seed=s).run(); factory reloaded each run; serial in-process, no sandbox, no workers.",
    "Verified all supplied UTF-8 code SHA-256 values and RC.startswith(N); CANDIDATE is exactly BASE + RC[len(N):], without edits or tuning.",
    "d = CANDIDATE.total_edge - BASE.total_edge. Summaries use full-precision differences; per_seed, worst and best round d to six decimal places. se is sample standard deviation (ddof=1) divided by sqrt(n).",
    "retail_diff and arb_diff are paired mean differences of retail_edge and arb_edge. check_values maps the first four seeds to unrounded BASE total_edge. Spread is cfg.competitor.spread_ticks; extremes are ranked on unrounded d, breaking ties by ascending seed.",
    "Failures include raised exceptions and SimulationResult.failed; failed pairs are excluded from statistics and have null d. complete requires all 500 successful pairs; per_seed lists every attempted seed in order.",
    "seconds_per_simulation is mean wall time for SimulationEngine construction and run(), excluding factory loading, downloads and report generation.",
    "Attempted 500 of 500 assigned seeds; 1000 simulation attempts; measurement loop elapsed 614.187703 seconds. Sources identify input code and simulator methodology; reported edges are local measurements, not quoted source results."
  ]
}