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","port_sha256":"6043444109ffc00b8b14f64435020034bf1edb44084ea51ff3fa9be17528b1b3","holdout":{"frozen_vs_start":{"n":8192,"mean_diff":0.003245882530587753,"se":0.003914954943238957},"frozen_vs_IB":{"n":8192,"mean_diff":0.5503179020855475,"se":0.010428421049060478},"start_vs_IB":{"n":8192,"mean_diff":0.5470720195549598,"se":0.010443134156081715},"seeds":[41010000,41018191]},"real":{"frozen_vs_IB":{"n":512,"mean_diff":0.5457838169650835,"se":0.03438573508545672,"sum":279.44131428612275,"sumsq":461.8626714089572,"worst5":[[8069008,-2.751334062587148],[8069056,-1.6837872916108836],[8068939,-1.4343408309442793],[8068798,-1.3097548584067908],[8068663,-1.1955212238803483]],"retail_delta":-0.3488276127155635,"arb_delta":0.8946114296806505,"retail_volume_delta":152.42476816043228,"by_quartile":{"q1":{"n":128,"mean_diff":0.667448072427141,"se":0.07303140378633223},"q2":{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performance and gas results here are local measurements, not leaderboard claims. Source artifact values are used only as explicitly labeled references.","Downloaded artifact JSON hashes equal URL identifiers. Decoded J5, IA, IB, KIT-B, original replica and differential source hashes were checked. IB code hash is 301941829a44bb60977bb28181a5e4bfa6544f3696763f987054789b2611d686.","Pinned checkout 6b6921f8d463314aa7c96234e1be25a25245f704; simulator wheel aedb68280aca34c110968f00148387c95885207913fb2cf19a1ab4c5cfd6887a; solc 0.8.24, optimizer runs 200, viaIR, Paris.","Gate B compares J5 minus IA on 7672000..7672511 against the task reference +0.876. Its replica and Rust market RNG paths differ; configuration draw order and ranges match MatchRunner._build_configs.","Port is the supplied IA port with J5 anchor literals parameterized and runtime TH instead of global PT. Delivered frozen_port exposes POLICY; use strat_init(S,POLICY,x,y) and strat_after(S,POLICY,is_buy,amount_x,amount_y,timestamp,reserve_x,reserve_y), fresh float64 S[40]. Its exact functions were used for Gate C and frozen holdout. IB uses its own supplied port and weights.","Freeze changed only head literals (rounded 1e-6), the 38 nonzero named constants, and three anchor literals. Freezing unchanged J5 reproduced its Solidity byte for byte. Feature scaling and all other literals stayed fixed.","Real markets were evaluated once per arm and seed, in disjoint chunks, each through amm_sim_rs.run_batch(candidate,VanillaStrategy,configs,8). Paired common seeds across arms are intentional; training generation seed blocks never repeat.","Retail and arbitrage edge decomposition reconstructs arbitrage from constant-product reserves and prior fees, including each policy's correct initialization fee, and checks reconstructed arbitrage volume against Rust. Standard errors use paired sample standard deviation / sqrt(n); sumsq is the sum of squared paired edge differences.","The 100 markets/s relay override applies: measured speed below 300 uses M=256. The holdout was accessed only after freezing, and never used to select weights.","Sources are in sources.json. The two JSON deliverables contain the frozen Solidity and port as base64(zlib(bytes)); no live network dependency is needed to decode them."]}