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","code_sha256":"adbf4f8c79c70cebfdecf2c0db65d869aa506068374223eddac636196b40b63a","params":{"W1":[[0.968898,1.846254,-1.464576,2.376163,-2.907313,-1.198001,-0.992214,1.972081,-5.1464,-0.005291,1.616674,-0.350025,0.34356,1.248566,0.784515,-0.89699,0.371235,-0.131863,-0.154588],[0.580255,0.926925,2.851628,2.879836,0.020337,-0.611959,-0.205248,-0.67171,0.007404,-0.087265,-0.167006,-0.94008,0.018866,-1.269607,-0.489405,1.809965,0.54051,-0.78381,0.257688],[0.895605,3.456537,0.353985,0.725692,1.651084,1.701281,-0.915139,1.199669,0.755814,-0.735333,0.161207,-2.712813,-0.535108,-0.223311,0.11699,0.578879,-0.42636,-1.022041,-0.778995],[-1.466514,-1.450544,1.38765,-0.197913,0.038095,0.787943,-1.675866,2.657962,-1.692967,-0.212903,0.784004,-2.070069,-1.856086,-0.119128,0.641388,0.745506,1.729944,0.418202,2.473425],[0.176495,1.681423,1.980338,0.019126,-1.413566,-0.460211,1.291266,1.216641,0.128932,-0.059131,0.049121,-2.088115,-0.178492,-0.523474,0.044434,-1.526752,1.966969,-0.54993,-0.188128],[2.756211,-0.771227,2.38138,-1.392067,1.685624,1.676557,0.063749,-0.256704,-1.153451,0.417277,-0.362867,3.13989,0.660621,-0.692381,-1.824914,0.474856,0.367589,1.589948,0.250952],[-0.638368,0.955689,0.062588,-3.528724,1.975149,-0.626174,-0.64635,-0.086724,0.802042,0.438141,0.206236,0.298363,-0.6629,0.9443,-0.12253,0.424729,-0.114895,0.760263,0.636029],[-2.476362,-1.706778,3.001719,2.280989,0.305088,-2.842021,-0.77679,3.402433,1.173379,-1.72892,2.769113,-2.130569,0.615641,0.743823,0.250192,2.019666,0.176731,-0.086345,-1.091575]],"b1":[1.981574,-1.774222,-2.562567,-2.274188,-1.423215,-1.605801,-3.008467,-1.120044],"W2":[[0.440293,-1.435794,0.562762,-0.486012,-2.924289,-0.772659,-3.036135,0.694401],[0.278064,-1.315563,-1.574501,0.331644,2.477294,-0.98257,0.942048,0.683368]],"b2":[2.006649,1.125179],"hidden_units":8,"input_count":19,"layout":"flat vector = W1 (8x19 row-major), b1(8), W2 (2x8 row-major: bid row then ask row), b2(2)","weight_fixed_point_scale":1000000,"feature_fixed_point_scale":1000000,"output_unit_fee":0.0001,"feature_order":["sigmaHat","lambdaHat","sizeHat","toxEma","actEma","direction","(spot-staleHat)/staleHat","signed_trade_ratio","arb_probability","first_in_step","uncertainty","min(silent,8)/8","anchor_mean","raw_amountY","step_trade_count","prev_bid_fee","prev_ask_fee","steps_since_arb_like_print","router_implied_vanilla_spot"],"feature_multipliers":[1000,2,500,500,500,1,500,500,2,2,1000000,1,500,0.05,0.5,333.333333,333.333333,0.125,500],"feature_offsets":[-1,-1,-1,-1,-1,-1,0,0,-1,-1,-1,0,-1,-1,-0.5,-1,-1,-1,0],"feature_clip":[-4,4],"hidden_relu_clip":[0,4],"toxicity_anchor":{"count_cap":674,"linear_k_wad":712696014807650816,"quadratic_k_wad":1295240753826310656}},"notes":["All supplied SHA256 values verified; setup wheel SHA256 verified. Input hashes: {\"HA\": \"99e3a2eceae0e5543d27473859e10b005d0ce0aa7067f2e1a24d1e0e4a7390fe\", \"IB\": \"301941829a44bb60977bb28181a5e4bfa6544f3696763f987054789b2611d686\", \"IB_port\": \"f63227c5e0f63633efd132d6fb402ede665e5c9cb24481911471e8dc20a3362d\", \"RS2_port\": \"9eac3553357528b06eeae3ed8d18283d83401e1968145ceba16be356a147e271\", \"T\": \"ebd9de9bf6af6e55d5e308fd15dbb88edec11fd684891d02a30aec185acd19b3\", \"replica\": \"1e4c44b4bffbdeed65872ee15d46dbde209bf5aa11014329d13d100507b4040c\"}","Pinned simulator checkout: 6b6921f8d463314aa7c96234e1be25a25245f704. Configs preserve MatchRunner._build_configs draw order and default ranges, substituting fresh seed. Each strategy runs separately against 30bps VanillaStrategy.","IB float port used unchanged. T is zero head weights. HA is its 13-input head padded with six zero columns. Replica market code unchanged outside STRATEGY import.","CMA uses normalized coordinates with block scales = 0.05 * frozen IB block RMS, scalar sigma initially 1 and capped before each ask at 0.5**(training_minutes/30). Elapsed search time sums active segments, excludes gaps, setup and initial monitor. State saved each generation. Curve entries are [training minutes, monitor mean edge minus T, normalized scalar sigma].","Best scheduled monitor point frozen; all weights rounded to 1e-6 and substituted into IB Solidity head. Source skeleton verified identical except head numeric literals. Holdout evaluated once after freeze, without selecting on holdout or real results.","All real comparisons use the same 512 fresh seeds, once per arm in 64-market chunks. Standard errors use paired sample standard deviation / sqrt(n). worst5 lists [seed,difference] from lowest paired differences.","The real wheel exposes volumes but no retail/arb edge split, so real retail_delta and arb_delta explicitly report volume Y differences. Replica holdout includes retail and arb edge differences.","No leaderboard submission or rank claim made. Measurements in this result were produced locally; cited artifacts establish input provenance."]}