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https://github.com/danrobinson/prediction-market-challenge at commit b244530ee2a6247b5f930830eeca9dd950da0e7e; all source files match the pinned archive.","T is the exact UTF-8 code string from https://api.imd.fun/artifacts/79af781a0f1882f2a291e045f803714b52128f9938480d54fb43360417b381ac. Candidate differs only by the specified ON line.","Python 3.13.5; serial in-process execution; no sandbox or workers. For each seed, runner.sample_config(ChallengeConfig(), ParameterVariance(), seed=s), then T followed by CANDIDATE on the same cfg and seed, each using a fresh loader.load_strategy_factory call and SimulationEngine(cfg, factory, seed=s).run().","d = CANDIDATE.total_edge - T.total_edge. Aggregate statistics use unrounded differences; per_seed, worst and best are rounded to six decimal places. se is sample standard deviation / sqrt(n); undefined values are null. Extremes are sorted by unrounded d, with ascending seed as the tie-breaker.","seconds_per_simulation gives the arithmetic mean wall-clock seconds for engine construction plus run(), excluding strategy loading, configuration sampling, and result writing.","All 500 paired results were measured locally in this run from the cited strategy and simulator, with neither strategy tuned and no prior results reused."]}