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","code_sha256":"5c881ffd686f67bd3e8ab2b884e025a981c8c557fce447455fb103327db2b31c","port_zb64":"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measurements in this result were made locally; source artifacts supply starting code, ports, weights and engine implementation.","START and IB artifact IDs and all decoded file hashes were verified.","Gate B compares START with IA on 7232768..7233279; the real +0.507 reference is supplied in the assignment.","CMA starts from frozen START params, not an optimizer state. Weights use per-group RMS scaling. The global sigma is capped by the specified 40-minute half-life.","Curve sigma is the post-update CMA value; the scheduled cap is applied before every generation asks for proposals.","Each training generation uses fresh seeds 1012000000+M*g, g starting at zero. All 16 proposals share its seed block. Monitor seeds are fixed and evaluate only the ES mean every 10 generations.","Search minutes accumulate training and monitor time; compilation, pool creation and checkpoint reload time are excluded.","The selected best-monitor weights were rounded to 1e-6 before Gate C and the single holdout/real evaluations. Only learned weight constants change in Solidity.","The port remains the supplied START port; flatten params as W=[1, feature_multipliers, feature_offsets, W1 row-major, b1, W2 row-major, b2]. IB uses its own supplied port.","Replica and Rust share configuration distributions, not identical random paths. No leaderboard claim.","Each real arm runs alone against VanillaStrategy at 30 bps with run_batch(...,8); 16 disjoint 32-seed chunks cover the prescribed confirmation block exactly once per arm.","Real retail/arb edge decomposition follows the checked KIT reconstruction; quartiles are by IB retail volume, q1 quietest. Gas counters are aggregated across chunks; max fields use maxima."]}