{"item":"e02-policy-table/rep-b","status":"complete_replica_only","headline":"Held-out replica gain over frozen mixture-B/table +2.135303 (SE 0.061160); remaining true-price oracle deficit 4.152408. No engine or leaderboard result.","remaining_deficit_assessment":"More than 2 replica edge units below the true-price oracle; the multi-point deficit is not closed.","decision":"Training-only parameter selection. This result cannot select a native entry; a Solidity port and independent engine confirmation are still required.","provenance":{"brief":{"url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/main/research/filter-brief.md","sha256":"0ef2200226b68aa58de6aad268442ba09ada710c54b3fb0ec35c77b491f78a4b"},"oracle_table":{"url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/main/research/oracle_table.json","sha256":"3e9d1fc8874c6d796d4c26948d486b587f2a6b5610b20fba99923a60954cf4b5"},"replica":{"url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/main/research/replica.py","sha256":"d079712fa1f4850ad8337e656e7ee8dbdde806cd4762d597fae50f547ef9c7c4"},"estimator":{"url":"https://api.imd.fun/artifacts/827590bb235808bd3789c89ad42e5038d2733d133c744455327a3e4275089b26","response_sha256":"827590bb235808bd3789c89ad42e5038d2733d133c744455327a3e4275089b26","all_embedded_hashes_verified":{"mf.py":"8adbd509efdac3e77ccde38d07a7272e9706b42ea4ecc926f77963e2a332445e","run.py":"7d7026c48cea6901ff3debebe5f552a7c263fa330a7f14448338a3df41837d33","agg.py":"d0e2f71bb48ab1467ca63d3af31d63f739678ce839408712f0165a3e69f77479","test_mf.py":"4192217a4bc758a6c0e5308d59224ea02a24dd217da012bd13fe5df824782ddc","sweep.py":"8e6613ef40efa930307bbea6a95acf4c438c15ce26b89afab127ee1b49b6efe5"}},"computed_claims":"Own runs of the embedded evaluator; primary numeric evidence is validation rows and pooled error sums/counts. No independent certification.","setup":{"checkout":"https://github.com/benedictbrady/amm-challenge","commit":"6b6921f8d463314aa7c96234e1be25a25245f704","script_url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/main/research/setup.sh","script_sha256":"dc7fa6a1e59f5b043d3954cf68d538318b7affaf5c0db3ca69a1822680f300d4","status":"success; StarterStrategy validated; no engine performance experiment"}},"policy":{"theta":[0.11673682199533918,0.4320854999155428,0.18942222088098645,0.11850577460622566,0.10075705904205952,0.08620575947154341,0.1714589542134512,-0.29690346844520776,-0.021840030607981675,0.22320545854985246,0.2337665097383401,-0.8548702862782424,0.8922540861207355,1.1551961718379862,0.2769505531879482,-0.750402994672444,-0.1628588498061043,-0.6242814527286578,-0.4995076972805937,0.10122609802635632,-0.597583140640253,0.18933957670525978,-0.3937566869930994,0.06233314510316826,0.20501687414282535,-0.1031616317349854,-0.2309947257025363,0.1754420491833727,0.14098491186212042,0.19497334406589217,0.13768581569314048,0.27496208363279595,-0.06694147799740041,-0.015239431792491043,-0.32454948255661326,-0.7557240012613221,-0.3166466780533231,-0.19718794402993817,0.07328596172888567,-0.6278367114503477,0.0578427003072841,-0.27292460838180876,0.029834642315455337],"weights":[-0.7964429348357562,-0.6292029622792723,-0.6755084508006541,-0.6397344075220726,-0.5588868925742497,-0.500705363823162,-0.11795128520633999,0.508842765603539,1.1571225808995385,1.6090783388894419,1.7875995338425739,2.234996051585341,3.511078962538523,3.9305011184231278,4.672060304495436,4.594458016184582,5.662724404222406,5.276523508853344,4.781602575876151,4.552261323011973,3.6218043361158165,3.4696317370078655,2.184954268192219,1.7675894051534182,1.5845439565398531,1.135402082644092,0.5775709653987653,-0.09725206894340596,-0.4513563707548968,-0.499995201774038,-0.6142832684377858,-0.5914230044132153,-0.9118312487854765,-0.8566286891240734,0.08357704487786789,-0.7557240012613221,-0.3166466780533231,-0.19718794402993817,0.07328596172888567,-0.6278367114503477,0.0578427003072841,-0.27292460838180876,0.029834642315455337],"inputs":"Frozen posterior mean and sd of z=ln(p/spot), own post-trade spot, and inferred arb probability. Absolute price scale is redundant: d=ln(spot/p_hat)=-E[z] up to floating-point roundoff. No true price, trade label, rival state or sampled run parameters in inference.","features":["u=d/0.003","q=clip(sd(z)/0.003,0,1)","v=tanh(u)","r=2*Pr(arb|observable history)-1","interaction features=[q,q*v,q*r,q*v*r]"],"units":"Mean, sd and displacement are natural log price units; 1 bp=0.0001. Knots at u=-8..8 (30 bps apart); quote offsets measured in 30 bps units; returned fees are fractions [0,0.1], order bid,ask.","layout":"weights[0:17]=ask knots; [17:34]=bid knots; [34]=common offset when Pr(arb)>0.5; [35:39]=ask interaction coefficients; [39:43]=bid coefficients.","bounds":"Each table knot is oracle knot +0.75*tanh(theta_i), at most 22.5 bps shift. Arb offset shift is 0.2*tanh(theta_34), at most 6 bps. Each added sd/probability quote interaction is 0.4*tanh(dot(coeff,features)), at most 12 bps. Fee clamp [0,0.1].","fee_formula":"Linear interpolation clamped at endpoint knots. askFee=clip(1-exp(d-0.003*askOffset),0,.1); bidFee=clip(1-exp(-0.003*bidOffset-d),0,.1). Initial bid=ask=.003.","closed_loop":"Every returned fee is fed to unchanged MixFilter.set_fees before the next callback; frozen inference/constants are never refitted.","frozen_filter_constants":{"KMAX":4,"SIG0":0.000945,"N0":200.0,"TAU_ROUTER":0.0015,"ROUTER":1,"PRETAIL":0.27,"RET_MU":2.2757322735539907,"RET_SD":1.3,"PIN_VAR":1e-12,"MINVAR":1e-12,"ARB_CONF":0.9}},"experiment":{"train_seeds":[31000,31255],"validation_seeds":[32000,32255],"ablation_seeds":[32000,32063],"ranges_inclusive":true,"steps":10000,"forbidden_seeds_used":false,"configs":"Exact replica.run defaults: Random(10000000+seed) draws size_mean U(19,21), lambda U(.6,1), sigma U(.000882,.001008) in this order. Price Random(seed), retail Random(seed+1), GBM log drift -sigma^2/2, retail lognormal sd=1.2 and log mean ln(size_mean)-.72. Init x=100,y=10000,p=100,K=1e6; rival fee .003.","pairing":"Every arm uses identical seed-dependent exogenous price, arrival, size and direction streams. All run independently against the .003 rival. Quotes affect later callbacks and posterior fee history.","arms":{"0":"fitted table + bounded uncertainty interaction, frozen mixture B","1":"unchanged mixture B and original oracle table, inferred arb threshold .5","2":"original oracle table, true fair price and true trade flag (privileged reference only)","3":"fitted weights with q forced to zero, no refitting, otherwise same filter and inferred arb threshold"},"freeze":{"utc":"2026-11-09T17:24:01.954736+00:00","training_generations":81,"weights_sha256":"c0977304cb8bb9e1927465ea5057c57b5789ee2e588b373a34d4b5c1ba3d7bae","policy_source_sha256":"4ba04a497271a93d96342331e7a21f8f38ffae95c32dcc5eb5dcf9fa51590202","estimator_source_sha256":"8adbd509efdac3e77ccde38d07a7272e9706b42ea4ecc926f77963e2a332445e","oracle_table_sha256":"3e9d1fc8874c6d796d4c26948d486b587f2a6b5610b20fba99923a60954cf4b5","replica_sha256":"d079712fa1f4850ad8337e656e7ee8dbdde806cd4762d597fae50f547ef9c7c4","selection":"Highest all-256-seed training mean; no validation outcomes observed."},"validation_started_utc":"2026-11-09T17:24:02.067715+00:00","validation_weights_sha256":"c0977304cb8bb9e1927465ea5057c57b5789ee2e588b373a34d4b5c1ba3d7bae","validation_evaluator":"Unmodified replica.py with stdlib policy.Arm; accelerator used only for training and parity checks.","uncertainty_ablation":"Zero sd feature q for all quotes on first64 validation seeds. This removes all added q/probability interactions, retaining the fitted table, frozen estimator and its original inferred-flag threshold. This is an intervention, not retraining or removal of the estimator variance."},"optimizer":{"algorithm":"Positive-weight full-covariance CMA-ES, embedded cma_std.py; no cma package dependency","dimension":43,"population":16,"initial_theta":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0],"initial_sigma":0.25,"rng_seed":2026110902,"generations":81,"initial_generation_cap":100,"intermediate_generation_cap":90,"effective_generation_cap":81,"budget_adjustment":"Stopped after the in-flight checkpoint segment near 80 generations when runtime rose from ~27s to ~45s, preserving the 60-minute item deadline; no validation had been observed.","evaluations":1313,"market_runs":336128,"market_steps":3361280000,"objective":"Mean closed-loop edge on ALL 256 training seeds, common random numbers. 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rounded to 4 decimal places; aggregates computed from unrounded observations. Edge in replica Y-value units."},"ablation":{"paired_on_minus_off":{"n":64,"mean":1.6282097387836982,"se":0.1392203373168361,"ci95":[1.3553378776426994,1.901081599924697]},"off_metrics":{"edge":{"n":64,"mean":510.2509872954494,"se":12.028621242297312,"ci95":[486.6748896605467,533.8270849303522]},"retail_mean":535.5717079370413,"arb_mean":-25.320720641591713,"rv_mean":74150.46490634313,"av_mean":22973.575912657383,"error_sum_log_sq":1.4947400358092604,"error_count":655718,"pooled_rms_bps":15.098168945266591,"coverage":0.94187440332582,"flag_error_rate":0.1078771667088596,"bid_fee_bps":37.34091069155763,"ask_fee_bps":36.51746021477304},"columns":["seed","sd_off_edge","on_minus_off"],"rows":[[32000,518.76799,3.1119],[32001,550.99622,0.91045],[32002,408.80662,0.49078],[32003,374.16278,1.61148],[32004,392.57904,1.78343],[32005,382.63698,3.09516],[32006,434.01474,1.74903],[32007,451.53254,-0.03883],[32008,602.93242,1.39479],[32009,612.2766,1.32027],[32010,440.49384,2.4534],[32011,646.81102,6.10861],[32012,675.20833,0.11015],[32013,449.62241,1.16979],[32014,432.68013,2.97761],[32015,443.54585,0.89404],[32016,482.42271,0.55341],[32017,425.74074,1.39284],[32018,594.63706,0.74448],[32019,485.48041,1.9165],[32020,623.93307,1.56949],[32021,555.64355,1.57832],[32022,664.6503,1.25511],[32023,574.75625,0.41679],[32024,555.81881,0.85461],[32025,551.03286,1.89568],[32026,434.52967,3.15683],[32027,521.00896,1.45955],[32028,633.7503,0.28131],[32029,412.34604,1.47164],[32030,381.70005,1.98548],[32031,457.11716,2.35915],[32032,624.90931,2.33264],[32033,435.67184,2.11],[32034,595.46769,0.91859],[32035,553.85271,0.69378],[32036,414.50396,1.92479],[32037,405.7362,2.03507],[32038,531.17848,0.10945],[32039,412.54755,2.16437],[32040,445.05883,1.87595],[32041,807.39607,-0.49801],[32042,534.45502,2.29342],[32043,369.85076,2.59545],[32044,522.30487,0.46731],[32045,654.38782,0.8208],[32046,637.04756,1.61247],[32047,432.36342,1.09556],[32048,500.89479,1.24699],[32049,598.92971,2.36073],[32050,478.32216,2.93095],[32051,636.52261,-1.10487],[32052,633.07651,2.02581],[32053,471.52455,1.69535],[32054,381.95984,2.14321],[32055,544.37936,0.80238],[32056,567.16348,3.71441],[32057,483.23215,1.57661],[32058,472.03268,1.39908],[32059,577.3371,0.75296],[32060,411.19226,3.24558],[32061,468.30595,2.95974],[32062,522.6793,2.29689],[32063,360.14324,1.57471]]},"checks":{"hidden_inputs":{"hidden_input_replay_callbacks":40902,"hidden_init_and_price_label_rival_changes":"fees and posterior identical","fee_history_feedback":"exact every callback","max_components":4,"max_observed_step_gap":15,"synthetic_fee_bounds_cases":10000,"ablation_zero_sd_equivalence":10000,"frozen_mf_hash":"verified"},"cma":{"sphere_initial":91,"sphere_final":5.557578546036823e-10,"resume_rng":"identical candidates","stdlib_eigen_reconstruction_maxerr":8.881784197001252e-16},"accelerator":{"full_length_markets":32,"training_seeds":[31000,31007],"modes":[0,1,2,3],"max_abs_metric_difference":4.885951057076454e-07,"frozen_table_exact_reference_comparisons":8,"no_fastmath":true},"training_reference_recheck":{"seeds":[31000,31255],"n_steps":10000,"max_abs_per_seed_edge_difference":1.0999201549566351e-10,"selected_mean_reference":526.7276561456182,"selected_mean_training":526.7276561456173,"mean_difference":9.094947017729282e-13,"paired_gain_reference":{"n":256,"mean":2.1299067663650035,"se":0.06846900006651326,"ci95":[1.9957075262346375,2.2641060064953695]},"seconds":80.22454476356506,"training_arms":{"0":{"retail_mean":555.4764773588547,"arb_mean":-28.74882121323658,"pooled_rms_bps":13.73448390248814,"error_count":2791777},"1":{"retail_mean":554.5731510677989,"arb_mean":-29.975401688545567,"pooled_rms_bps":15.206482870320954,"error_count":2639664}}},"stdlib_offline":{"stdlib_site_disabled":true,"markets":11,"steps":10000,"max_error_vs_rounded_rows":4.116925754260592e-05,"python":"3.13.5"}},"cost":{"state":"Frozen filter <=4 Gaussian components (12 numbers), 14 scalar state fields including diagnostics/last-pin pair; each intermediate mixture <=5 components (multiple lists may coexist); policy has 43 read-only weights. Constant state per market.","compute":"Each callback: <=400 silent per-step diffuse/truncate passes plus one bulk pass, one first-event update, <=one merge over 10 pairs, two 17-knot interpolations and bounded four-feature interactions. No new history buffer.","gas":"Not measured; frozen 400-step cap may be expensive in Solidity. No port, gas bound, native fee equality or engine score claimed."},"runtime_seconds":{"training_segments_including_compile":2453.4269268512726,"validation":62.03033232688904,"task_elapsed_at_pack":3507.442841},"dependencies":{"inference_and_reference_evaluation":"Python standard library only; tested under CPython 3.12.16 and offline fallback check under 3.13.5","optional_training_acceleration":{"numpy":"2.5.4","numba":"0.68.1","llvmlite":"0.50.0"},"optimizer_fallback":"Embedded Jacobi eigensolver and standard-library full-covariance CMA-ES; trainer falls back to reference replica if optional packages are unavailable. No network needed for delivered inference/evaluation."},"numeric_dead_ends":[{"experiment":"Initial generation, all 16 random candidates below frozen table","best_delta":-2.142424022657906,"worst_delta":-5.3882593313915095},{"experiment":"Remaining held-out oracle deficit","mean":4.152408405771501,"ci95":[4.006085024202832,4.29873178734017]}],"limitations":["Replica results do not establish leaderboard rank, RS2 paired gain, or an engine entry. RS2 code was not fetched or used.","Fixed estimator and this bounded interaction family may leave a material price-estimation deficit. No changes to classifier, sigma adaptation, likelihoods or mixture constants.","Confidence intervals use 1.96 * sample standard deviation of per-seed paired differences / sqrt(n); these are descriptive normal-approximation replica intervals with no family-wise coverage claim.","Oracle error counts are zero because no estimated price is used there; its RMS is null. Pooled RMS for learned/frozen arms weights every own callback, so callback populations differ with policy."],"source":{"encoding":"base85 of an LZMA-compressed UTF-8 JSON object mapping filenames to complete source 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00F~YsGtG>wY@v{vBYQl0ssI200dcD","decoded_archive_sha256":"8f4d7de17c98df995abf421e51aa3a784e155e9783086b214bf58947e35a9c7e","file_sha256":{"mf.py":"8adbd509efdac3e77ccde38d07a7272e9706b42ea4ecc926f77963e2a332445e","replica.py":"d079712fa1f4850ad8337e656e7ee8dbdde806cd4762d597fae50f547ef9c7c4","oracle_table.json":"3e9d1fc8874c6d796d4c26948d486b587f2a6b5610b20fba99923a60954cf4b5","policy.py":"4ba04a497271a93d96342331e7a21f8f38ffae95c32dcc5eb5dcf9fa51590202","evaluate.py":"69efc88b18915de825f0e1fbf9d1bbdea790b6cb2018eb368d4b8ec46ee4bf8a","accelerate.py":"bdf7718e6cd80c866ae8ecd5fd4998e95520258e2065918cc24f7e6bdc4abeeb","cma_std.py":"5999b60dcd49d841415cb618a92f0baeb9f16569180d8e3ff862fe5479f006c1","train.py":"eb87a1cb44f8bc0933b1b5764f33f1ef0ac052044b4f7db21fc733d739dfd1b6","test_policy.py":"84f7e3a35b3a1a35eda683d00fe37c2307e0e8f03d441e2a8be74df1a80366be","check_fast.py":"28099b12f2f97459abff36834de778affb6537d09327ac910a8064044b3f288f"},"extract":"import json,base64,lzma,pathlib,hashlib,sys\nr=json.load(open(sys.argv[1]));b=lzma.decompress(base64.b85decode(r[\"source\"][\"archive\"]));assert hashlib.sha256(b).hexdigest()==r[\"source\"][\"decoded_archive_sha256\"];d=pathlib.Path(sys.argv[2]);d.mkdir(parents=True,exist_ok=True)\nfor n,s in json.loads(b).items():\n assert hashlib.sha256(s.encode()).hexdigest()==r[\"source\"][\"file_sha256\"][n];(d/n).write_text(s)\n","run":"After extraction: python evaluate.py /path/to/result.json 32000 32256 validation.json. No external packages required. Training: python train.py 81, optionally with pinned accelerator packages; checkpoints under scratch/."}}