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","code_sha256":"fc5472952e3eaea3d442c75d78e45bc75fb51765b2bb45e0dcbde2afbc0a1b36","port_zb64":"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reported performance, differential and gas figures are local measurements. External sources identify pinned inputs; no leaderboard submission or ranking claim.","CG head weights fixed throughout; only the 33 named constants searched. CA port modified to pass constants as runtime parameters and restore T constants for CG gates; frozen port preserves supplied W217 API.","First segment scored raw CMA genotype means before boundary conversion was corrected. Those invalid mean scores were discarded; no invalid policy was frozen. Subsequent mean monitoring uses the bounded phenotype. This is a protocol deviation.","CMA_stds=.5 with sigma0=.06 gives initial constants step .03. Weight CMA_stds are inapplicable because head weights are fixed.","Retail/arb decomposition reconstructed using kit logic with each arm initial BASE_FEE; total edge comes directly from Rust.","Holdout consumed exactly once after freeze. over_IB is over_T minus the requested fixed 1.7690 reference, not an independently simulated IB comparison.","Nine kit unit tests passed. Search checkpoints saved after every generation. Each execution segment limited to 470 seconds.","Curve contains at most 30 evenly spaced valid monitor records; detailed per-arm deltas are retained for holdout and real confirmation.","Only requested JSON outputs delivered. Installed evaluation dependencies are disposable and not embedded as an offline runtime; Solidity relies on challenge base imports. Frozen source and port are embedded with hashes."]}