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","code_sha256":"48a493006cbc6e49f3559d0c9dfcafff35ad3a031e80d6bc368e192bcf83320c","port_zb64":"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","port_sha256":"831a087dea55262f1e334e6800153b2d276208994ae66e9a001a705f3c60fd64","params":{"architecture":"19-16-2; 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rounded 1e-6","new_b1_W2_zero":true,"evm_stream_check":{"passed":true,"sequences":50,"swap_callbacks":100000,"initialization_callbacks":50,"IA_code_sha256":"956566e95f46dc1ed5980fae5e550de7b9da10f9b3ad8eed62f265682cfcecf2","wide_initial_code_sha256":"fdbd29e7c0ab2409b89174f06b6c14f6da241bd9995b245f3014989b92fafe7f","evm_fee_stream_sha256":"5965e509a5b9eaf0027de30cd849a88b9d4348292f23155a758ce78fab8ebbfb"}},"nonzero_compile":{"passed":true,"bytecode_bytes":17197,"seconds":22.229944864986464,"hidden_units":16,"units_per_function":8},"notes":["Input downloads and all decoded source hashes checked against the supplied IDs and hashes; external source claims are cited in sources.json. Performance and parity metrics are local measurements.","IA frozen params, rather than its last CMA mean, supply the original eight units. Eight new W1 rows are normal(0,0.1) with RNG seed 20260323; new hidden biases/output weights are zero. All weights are quantized to 1e-6.","IAD applies DIET storage packing to IA without altering fee arithmetic or the slot15 last-arb timestamp. Slots 0,3,6,13 pack the same fields as DIET; extra IA features retain their original formulas and scaling.","Widened Solidity sums both eight-unit partial accumulators before the final signed division, preserving IA rounding. No function evaluates more than eight hidden units.","CMA-ES checkpoints every generation; training uses common seeds for all proposals. Every tenth generation monitors the decade training winner, current generation winner and CMA mean. Freeze chooses the best historical monitor result including initial IA.","Training/monitor/holdout use the fast replica, whose random streams intentionally differ from Rust. Paired comparisons use identical seed/config draws within each engine, not identical paths between engines.","Real arms run separately versus VanillaStrategy with canonical MatchRunner config draw order. Reserved confirmation block used once per arm after freezing; no confirmation-dependent policy changes.","Retail and arb are reconstructed using the kit decompose function, cross-checked against Rust arb volume; their deltas add to edge delta.","Curve samples at most 20 monitor rows across the run and includes the winning monitor row; curve_rows_total reports the unsampled count. Holdout evaluated once, after freezing.","No leaderboard submission or top-ten ranking claim. Runtime requirements are the supplied goal SETUP Python packages and pinned solc 0.8.24; binary dependencies are not embedded in this JSON.","Compact result omits optional measurement source bundle to stay under 64000 bytes."],"dependency_versions":{"numpy":"2.5.4","numba":"0.68.1","cma":"4.5.0","py-solc-x":"2.1.0","pyrevm":"0.3.7","python":"3.12.16","solc":"0.8.24","amm_sim_rs":"0.1.0.post1"},"baseline_T_parity":{"passed":true,"sequences":50,"swap_callbacks":100000,"initialization_callbacks":50,"max_abs_fee_difference_bps":1.2216616607219066e-09,"threshold_bps":0.01,"fee_comparisons":200100,"share_above_0_01_bps":0.0,"seeds":[310000,310049]},"port_api":"S=np.zeros(40); strat_init(S,W,x0,y0); strat_after(S,W,is_buy,amount_x,amount_y,timestamp,reserve_x,reserve_y). W=TH_CANDIDATE or TH_T/TH_HA/TH_IA; all quantities in real units. HEAD_START=39, head length 354."}