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clipped ReLU [0,4], inputs clipped [-4,4], output correction in 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","code_sha256":"dd53db1fbe42628e040c6c7b7a82689867ab601263c5e740506299a3a186b38c","port_zb64":"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performance, differential and gas results are local measurements from this run. No leaderboard placement is claimed.","Pinned checkout 6b6921f8d463314aa7c96234e1be25a25245f704 and wheel aedb68280aca34c110968f00148387c95885207913fb2cf19a1ab4c5cfd6887a; downloaded artifact JSON hashes equal their URL identifiers; all provided decoded code/port hashes checked.","Gate B: START minus IA on seeds 7672000..7672511, compared with real +0.876. Gate A/C: 50 sequences of 2000 swap callbacks each, thresholds 0.01 / 0.1 bps.","Replica speed measured steady-state with two processes and no concurrent workloads. This item uses the requester override: 100 markets/s threshold, 256-market training blocks below 300 markets/s.","Training checkpoint preserves full CMA covariance, mean, sigma and numpy RNG across commands shorter than eight minutes. Weights use per-block RMS scaling from frozen J5. Constant exponents clipped to [-1,1], as J5 search.settings specifies; nine decays parameterized through 1-d.","Frozen weights rounded to 1e-6 before Solidity and port confirmation; only head, declared nonzero constants and three anchor literals changed. START freeze self-test reproduced its Solidity byte for byte.","Port array layout: head-enable, 19 feature multipliers, 19 offsets, 178 weights (W1,b1,W2,b2), 3 anchor constants, TH_VALUES. Frozen array is port.FROZEN_POLICY. Call strat_init(state, FROZEN_POLICY, x, y) and strat_after(state, FROZEN_POLICY, ...), fresh float64 state[40] per deployment. Replica source imports sibling port.py; call run_many(port.FROZEN_POLICY,seeds,procs). Requires numpy/numba as in SETUP.","Holdout evaluated once after freezing on 41010000..41018191; IB used its own supplied port and scaling. Replica random streams reproduce distributions, not Rust random paths.","Real confirmation evaluated once per arm on seeds 8081920..8082111 in disjoint chunks of [32, 32, 32, 32, 32, 32] markets. Config draws follow MatchRunner._build_configs with RNG seeded by market seed.","Real arb edge reconstructed from invariant k, prior end-step spot and prior fees, starting with each arm actual BASE_FEE; recovered arb volume checked against simulator totals. Retail edge = total edge - arb edge.","Quartiles rank the 192 completed seeds by IB retail volume, q1 quietest. Paired SE uses sample standard deviation / sqrt(n); sumsq is the uncentered sum of squared paired differences. worst5 lists the five lowest paired differences.","Submitted Solidity retains the original base imports supplied by the pinned challenge repository. Setup installations and scratch checkpoints are not submitted.","Gates A/B/C and observed gas checks passed. valid=false because the full required 512-seed real confirmation was not completed. Partial real measurements are reported with their actual n; no missing results were inferred or invented.","No monitored ES mean improved on START; the frozen policy retains START byte for byte. Training is not claimed to have improved the policy."],"observed_gas_valid":true}