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clipped ReLU [0,4]; input clip [-4,4]; output bps added to T-path 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IB arm used IA vector layout incorrectly; it was not the IB policy and was discarded. 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All weights were frozen before these evaluations; none selected from 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quietest.","max_abs_arb_volume_reconstruction_error":{"IB":5.140266512171365e-05,"START":6.821795977884904e-05,"frozen":7.672134233871475e-05},"code_sha256":{"IB":"301941829a44bb60977bb28181a5e4bfa6544f3696763f987054789b2611d686","START":"dd53db1fbe42628e040c6c7b7a82689867ab601263c5e740506299a3a186b38c","frozen":"3999afb6acdcd3bdb6dbee03603c4a78dcd3979d55a30f3560809ceab6671846"},"seconds":{"IB":233.21400788496248,"START":213.51878008199856,"frozen":125.8595288048964},"valid":true},"gas":{"IB":[{"role":"Baseline","callback":"afterInitialize","calls":512,"ok":512,"max_ok_gas":21796,"sum_ok_gas":11159552,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"afterSwap","calls":5549100,"ok":5549100,"max_ok_gas":22592,"sum_ok_gas":125203295856,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"getName","calls":512,"ok":512,"max_ok_gas":21526,"sum_ok_gas":11021312,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterInitialize","calls":512,"ok":512,"max_ok_gas":243227,"sum_ok_gas":124532224,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterSwap","calls":5554065,"ok":5554065,"max_ok_gas":232231,"sum_ok_gas":750322530111,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"getName","calls":512,"ok":512,"max_ok_gas":21735,"sum_ok_gas":11128320,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0}],"START":[{"role":"Baseline","callback":"afterInitialize","calls":512,"ok":512,"max_ok_gas":21796,"sum_ok_gas":11159552,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"afterSwap","calls":5541584,"ok":5541584,"max_ok_gas":22592,"sum_ok_gas":125033557780,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"getName","calls":512,"ok":512,"max_ok_gas":21526,"sum_ok_gas":11021312,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterInitialize","calls":512,"ok":512,"max_ok_gas":243234,"sum_ok_gas":124535808,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterSwap","calls":5574496,"ok":5574496,"max_ok_gas":237387,"sum_ok_gas":754911389529,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"getName","calls":512,"ok":512,"max_ok_gas":21742,"sum_ok_gas":11131904,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0}],"frozen":[{"role":"Baseline","callback":"afterInitialize","calls":512,"ok":512,"max_ok_gas":21796,"sum_ok_gas":11159552,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"afterSwap","calls":5533787,"ok":5533787,"max_ok_gas":22592,"sum_ok_gas":124857741004,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"getName","calls":512,"ok":512,"max_ok_gas":21526,"sum_ok_gas":11021312,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterInitialize","calls":512,"ok":512,"max_ok_gas":243234,"sum_ok_gas":124535808,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterSwap","calls":5574080,"ok":5574080,"max_ok_gas":237402,"sum_ok_gas":754963423420,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"getName","calls":512,"ok":512,"max_ok_gas":21742,"sum_ok_gas":11131904,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0}]},"valid":true,"input_hashes":{"START_json":"fe2320b5c091489337b3eb06bcbaea19bf4a8af09d959d67504ba63184f1dab6","START_code":"dd53db1fbe42628e040c6c7b7a82689867ab601263c5e740506299a3a186b38c","IA_json":"df0ddfdf122c88641513dd179980fce475f42a912a184f812d213f27db7c14df","IA_port":"b29cd2a078b4c3fc57945a79e927624dd346c44d8cc149dae43f4929aa6d736b","IB_json":"afd5183e9ff3235334e041c00b0cd19079599a2c6464db95f8c1586712105557","IB_code":"301941829a44bb60977bb28181a5e4bfa6544f3696763f987054789b2611d686","IB_port":"f63227c5e0f63633efd132d6fb402ede665e5c9cb24481911471e8dc20a3362d","replica_source":"1e4c44b4bffbdeed65872ee15d46dbde209bf5aa11014329d13d100507b4040c","differential_source_artifact":"d845a4b94eab87f23956fd1939c0135d955df212d1f3037f2a761c178cef7a0e","KIT_B_json":"48cd6a10f39fc22a79c5f12398474bd65282803d59314819acd586f187015808","wheel":"aedb68280aca34c110968f00148387c95885207913fb2cf19a1ab4c5cfd6887a","checkout":"6b6921f8d463314aa7c96234e1be25a25245f704"},"notes":["All newly reported performance results are local measurements, not independently certified scores or leaderboard claims. Gate B target +0.876 is the historical J5 real result supplied in the brief. Input sources and exact quotes are in sources.json.","The 100 markets/s override was applied. Measured throughput was below 300, so every generation used 256 markets. Search ran to the stated cutoff; held-out and real results were not used to select the frozen point.","Port is the supplied IA port, with only the three anchor literals parameterized, TH passed via the policy vector, and Numba caching enabled. IB holdout uses its supplied separate port, with caching decorators only.","Port vector W = [1, feature_multipliers(19), feature_offsets(19), W1 row-major(152), b1(8), W2 row-major(16), b2(2), anchor_count_cap, anchor_linear_k, anchor_quadratic_k, TH_VALUES]. Replace the 38 named TH constants with params.constants[name][1]. Constants store [original IA value, frozen value]. Fresh state is np.zeros(40). Call strat_init(S,W,100.,10000.) then strat_after(S,W,is_buy,amount_x,amount_y,timestamp,reserve_x,reserve_y). All amounts are real units.","Freeze changes only head literals (1e-6 precision), the 38 searched named declarations, and the three anchor literals. Starting freeze reproduced J5 Solidity byte for byte. Frozen constants were read back from Solidity for the final port vector.","Replica and real use matching configuration distributions but different random price/retail paths. All three arms in each comparison run alone versus 30 bps Vanilla, never head to head.","Real retail/arb edges use KIT-B constant-product reconstruction with the actual afterInitialize fees for each arm; reconstructed arb volume is checked against engine totals. The reported maximum reconstruction error is in real.","Frozen and START holdout blocks were each evaluated once. An initial IB arm with the wrong vector layout was discarded; the correct IB policy was verified against EVM and evaluated once, retaining frozen/START rows. This correction is detailed in holdout. Real blocks were each evaluated once per arm in disjoint 64-seed chunks with eight workers. Any OOG, revert, other halt, transaction error, malformed return, or afterSwap gas peak >245000 invalidates the result.","Decode *_zb64 with base64 then zlib. Solidity imports are included in runtime_sources_zb64. runtime_sources_zb64 is a JSON filename-to-text map; it includes the frozen policy vector and the replica shell used here. External Python numerical packages and the real simulator are setup prerequisites, not embedded binaries."],"runtime_sources_zb64":"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","evaluation_sources_sha256":"0854807deecaba5bae1413a6664ee50fd2eb5b50cb30074e8aea4b7e3818cb1e","versions":{"numpy":"2.5.4","numba":"0.68.1","cma":"4.5.0","py-solc-x":"2.1.0","pyrevm":"0.3.7","amm-sim-rs":"0.1.0.post1"},"performance_assessment":"The real confirmation does not establish a gain over START: frozen minus START is -0.0158573 with SE 0.0261406. The frozen point remains the prescribed best-monitor selection; no selection used holdout or real results.","measurement_hashes":{"gate_B_rows.npz":"2912de1e979f13857b396422feb7982a8854e521e2c3a70fe3ab5b301ada00a8","holdout_rows.npz":"ca0fddb3b7f8874b77a9e3d1bc73e3e235a088b31dec2c8ceda7498242b8155a","real_rows.npz":"69b2632d57e5e358acc780ae1f669c205b0a7042ed4bc525f50662081c77952e"}}