{"item":"config-oracle","batch":"e07-c-quotient","status":"stopped_at_step1_bound_below_0.04","conclusion":"NULL RESULT. Knowing each run's true sigma, lam and mean order size (NON-blind oracle, tuning seeds 65500..65755 only) gains nothing measurable over BASE: per-step filter variance = sigma^2 alone is -0.0035 se 0.0084; the best of 30 coordinate-search trials of shared bid/ask fee offsets linear in (lam-0.8), (sigma_bps-9.45), (size-20) is cz=+0.03125 bps per unit of size, -0.0012 se 0.0088. Every offset tried with a larger coefficient lost (up to -0.18). The oracle bound is under 0.04 (the best is <= 0 within noise), so per the brief Step 2 (blind estimates) was not built and no holdout was scored. Nothing here goes into a contract.","oracle_bound":{"label":"NON-blind: runner hands true (sigma, lam, size) at init; tuning seeds only","seeds":[65500,65755],"best_params":{"var":1,"cl":0.0,"cs":0.0,"cz":0.03125},"best_vs_base":{"n":256,"mean_diff":-0.0011967588505610305,"se":0.008755875537037194,"sum":-0.3063702657436238,"sumsq":5.005081118430314,"worst5":[[65666,-0.5679925910588963],[65723,-0.5548564875081752],[65742,-0.39204265559919804],[65529,-0.3285502512616745],[65720,-0.32264240892709495]]},"variance_only_vs_base":{"n":256,"mean_diff":-0.0034619207265842444,"se":0.008410576003949679,"sum":-0.8862517060055666,"sumsq":4.62083098067501,"worst5":[[65571,-0.6288991917636508],[65666,-0.4587983703864893],[65718,-0.3819974229405716],[65742,-0.3341269895120149],[65567,-0.33028604059995814]]},"threshold":0.04,"passes_threshold":false,"note":"best_params is the argmax of a 30-trial search (plus 1 rule-off parity run) on the same 256 seeds, so -0.0012 is itself optimistically biased; the true bound is <= ~0 + noise."},"exact_rule":"Tested rule (oracle form, not recommended): at afterInitialize take the run's sigma (fraction per step), lam (retail orders per step) and size (mean order size, Y). (a) In the Gaussian filter replace the constant per-step variance SIG2=(9.45e-4)^2 by sigma^2 wherever it is added (each silent step and the current step). (b) Compute off_bps = cl*(lam-0.8) + cs*(sigma*1e4-9.45) + cz*(size-20) once; after every fee computation (init and each afterSwap) add off_bps*1e-4 to BOTH bid and ask fee before BASE's WAD conversion and clamp to [0, 1e17] (stalerival.fee). With var off and cl=cs=cz=0 this is BASE bit for bit (checked on 8 seeds 65500..65507, both through run.py and through the oracle runner). The engine never gives a contract sigma, lam or size, so a port would need the blind estimators of Step 2, which were not built because the oracle bound failed.","frozen_parameters":null,"frozen_parameters_note":"Nothing frozen: Step 2 not run. Best oracle tuning point, for reference only: {\"var\": 1, \"cl\": 0.0, \"cs\": 0.0, \"cz\": 0.03125}","base":{"policy":"stalerival:Policy","options":"a0=0.35 ainf=0.35 soft=1 qm=qm_k1e-5.json","sha256":"176f8115fb67d99340f1de1e6994042dfaa41f830c22e000595df3377cc6a2b3","sha256_verified":true,"source_artifact":"https://api.imdnotdead.fun/artifacts/806404e8de0d3fee0641a55560fee2001cdf19cceefd05c7b23b9b486faa263f"},"quotient_py_sha256_verified":"ff9afbb71f1a030333cd9b8ce283a83d8e5d423fdae1726d1f3d480685744efb (fetched and checked; not used by this experiment)","setup":{"fetch":"34 files, 0 mismatched","tellpol_gate_seed10000_edge":446.7525003520403},"parity_rule_off":"8 seeds 65500..65507: cfgor:Policy var=0 through unmodified run.py gives rows identical to stalerival:Policy; oracle runner with base and var=0 gives edge differences of exactly 0.0 on all 8.","tuning_trials":[{"params":{"var":0,"cl":0.0,"cs":0.0,"cz":0.0},"n":256,"mean_diff":0.0,"se":0.0},{"params":{"var":1,"cl":0.0,"cs":0.0,"cz":0.0},"n":256,"mean_diff":-0.003462,"se":0.008411},{"params":{"var":1,"cl":4.0,"cs":0.0,"cz":0.0},"n":256,"mean_diff":-0.137297,"se":0.017879},{"params":{"var":1,"cl":-4.0,"cs":0.0,"cz":0.0},"n":256,"mean_diff":-0.175143,"se":0.020546},{"params":{"var":1,"cl":0.0,"cs":1.0,"cz":0.0},"n":256,"mean_diff":-0.108125,"se":0.015412},{"params":{"var":1,"cl":0.0,"cs":-1.0,"cz":0.0},"n":256,"mean_diff":-0.097789,"se":0.01498},{"params":{"var":1,"cl":0.0,"cs":0.0,"cz":0.5},"n":256,"mean_diff":-0.059325,"se":0.01422},{"params":{"var":1,"cl":0.0,"cs":0.0,"cz":-0.5},"n":256,"mean_diff":-0.140007,"se":0.014851},{"params":{"var":1,"cl":2.0,"cs":0.0,"cz":0.0},"n":256,"mean_diff":-0.048551,"se":0.013017},{"params":{"var":1,"cl":-2.0,"cs":0.0,"cz":0.0},"n":256,"mean_diff":-0.081773,"se":0.013144},{"params":{"var":1,"cl":0.0,"cs":0.5,"cz":0.0},"n":256,"mean_diff":-0.053616,"se":0.010698},{"params":{"var":1,"cl":0.0,"cs":-0.5,"cz":0.0},"n":256,"mean_diff":-0.051757,"se":0.011848},{"params":{"var":1,"cl":0.0,"cs":0.0,"cz":0.25},"n":256,"mean_diff":-0.022008,"se":0.01047},{"params":{"var":1,"cl":0.0,"cs":0.0,"cz":-0.25},"n":256,"mean_diff":-0.070075,"se":0.011766},{"params":{"var":1,"cl":1.0,"cs":0.0,"cz":0.0},"n":256,"mean_diff":-0.022743,"se":0.010671},{"params":{"var":1,"cl":-1.0,"cs":0.0,"cz":0.0},"n":256,"mean_diff":-0.04496,"se":0.010909},{"params":{"var":1,"cl":0.0,"cs":0.25,"cz":0.0},"n":256,"mean_diff":-0.038597,"se":0.008694},{"params":{"var":1,"cl":0.0,"cs":-0.25,"cz":0.0},"n":256,"mean_diff":-0.020999,"se":0.010429},{"params":{"var":1,"cl":0.0,"cs":0.0,"cz":0.125},"n":256,"mean_diff":-0.015587,"se":0.009336},{"params":{"var":1,"cl":0.0,"cs":0.0,"cz":-0.125},"n":256,"mean_diff":-0.041748,"se":0.008909},{"params":{"var":1,"cl":0.5,"cs":0.0,"cz":0.0},"n":256,"mean_diff":-0.020219,"se":0.009487},{"params":{"var":1,"cl":-0.5,"cs":0.0,"cz":0.0},"n":256,"mean_diff":-0.021835,"se":0.008643},{"params":{"var":1,"cl":0.0,"cs":0.125,"cz":0.0},"n":256,"mean_diff":-0.012139,"se":0.008471},{"params":{"var":1,"cl":0.0,"cs":-0.125,"cz":0.0},"n":256,"mean_diff":-0.009446,"se":0.009272},{"params":{"var":1,"cl":0.0,"cs":0.0,"cz":0.0625},"n":256,"mean_diff":-0.006437,"se":0.00854},{"params":{"var":1,"cl":0.0,"cs":0.0,"cz":-0.0625},"n":256,"mean_diff":-0.021106,"se":0.008638},{"params":{"var":1,"cl":0.25,"cs":0.0,"cz":0.0},"n":256,"mean_diff":-0.009972,"se":0.009137},{"params":{"var":1,"cl":-0.25,"cs":0.0,"cz":0.0},"n":256,"mean_diff":-0.014932,"se":0.008805},{"params":{"var":1,"cl":0.0,"cs":0.0625,"cz":0.0},"n":256,"mean_diff":-0.012733,"se":0.009044},{"params":{"var":1,"cl":0.0,"cs":-0.0625,"cz":0.0},"n":256,"mean_diff":-0.005371,"se":0.008351},{"params":{"var":1,"cl":0.0,"cs":0.0,"cz":0.03125},"n":256,"mean_diff":-0.001197,"se":0.008756}],"tuning_search":"coordinate search from (var=1, 0,0,0); steps cl 4, cs 1, cz 0.5 bps per unit; each coordinate tried +/-step, accepted only if mean_diff vs BASE improved; steps halved after a round without improvement; 5 rounds. Trial 0 is the rule-off parity run (exactly 0).","run_parameters_on_tuning_seeds":{"sigma_bps_range":[8.821630131157038,10.069656821980171],"lam_range":[0.6010574994962302,0.9994947999014705],"size_range":[19.004069342080314,20.99735488161326]},"holdout":null,"holdout_note":"Not run, by the brief: the oracle bound is under 0.04, so no blind variant was frozen and seeds 10000..12047 were not scored. The check BASE - tell_qm.json = +0.0886 was therefore not performed here.","rows_zb64":null,"tuning_rows_zb64":"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","tuning_rows_format":"base64(zlib(JSON [[seed, best-oracle-variant edge, BASE edge], ...])) on tuning seeds 65500..65755 (NOT holdout rows; NON-blind)","tuning_rows_sha256":"5703566511b35e38d9fe82ff095afcffa664eea8a2eed2a301d324fd76042d76","contract_cost_per_callback":{"oracle_rule_as_tested":{"note":"not implementable on the engine (needs sigma, lam, size the engine does not give)","worst":{"add":2,"compare_clamp":2,"mul":0,"storage_read":1},"mean":{"add":2,"compare_clamp":2,"mul":0,"storage_read":1},"detail":"offset computed once at init (3 mul, 3 sub, 2 add); per callback add it to bid and ask and re-clamp; sigma^2 replaces a constant at no cost"},"blind_estimators_step2":"not built (stopped at Step 1); no counts measured"},"code_zb64":"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JSON map path->text)); sha256 is of the decoded JSON bytes","code_sha256":"3ca097eb47afbf0eefab189899822f937f404fc8a60ad811d48744eee0b38ade","code_files_sha256":{"amm/cfgor.py":"e7f47f57e27943780b2a00e828832d64641136c5983ca34cad3016ca5bf0ccb6","orun.py":"6c184f1fc70f98f18125923b354313c75ac34f178100eabbc0ebfb242494c1cb","tune.py":"5a91a4c97360c401eb2360eb2548cfd5cbc843bcafea16a1e00f557a258342d6","s2.sh":"fec414f1efc4f62cc4e7e17c3723c84b7b93e6bd0c5d436afa3be0d939aeb8d1","finalize.py":"f3c8e40e306ff56535f6765a13937552685381dce24cd1444b2eaeda99b5d023"},"completed_seeds":{"tuning":[65500,65755],"tuning_runs":"256 seeds x (BASE + 31 trials)","parity":[65500,65507],"holdout":[]},"remaining_seeds":{"holdout":"none required: 10000..12047 skipped by the stop rule"}}