{"item":"rc-scale","batch":"e09-rival-cut","credit":"Taylor (gtmcknight): replica, Gaussian filter, solved policy and qm tables; github.com/gtmcknight/amm-sim @4812a6382311624e1506aca131ca35c378f930d9, research/solved, README first. LEAN tell and o1-b port inherited from the verified TCA/LB4 artifacts.","status":"complete: null result; zero-change control selected","input_sha256_checks":{"tca":{"download_sha256":"dc359635b5851de9f5b3ecf81dc2107d46acd5dbe67e0be234bcfbe0c8a488e7","bundle_sha256":"546b440855726c3cd2231e4879e0002dda182dc609ee9c5155c04e4790ca6fdb","bundle_hash_pass":true,"manifest_hash_pass":true,"all_manifest_files_pass":true,"manifest_files":32},"lb4":{"download_sha256":"93cc15561f172c49c8bce174143333ede904fdbfcf51276cbbeb514d4f5b614e","bundle_sha256":"f368c459fec21abaa30e179ffbf03cfbe1c7b194f1ad8b07de3637892d06e9f1","bundle_hash_pass":true,"all_overlay_and_unchanged_manifest_files_pass":true},"gates_py_sha256":"603280c1f595ca163ffaf2ba1ebdc7945fdb08dabae67fc53c922d39e1cce604","blob_sha256":"3ac7cb8811ecfb6a17f499aa4e9b70dd55f7fb6432b3aec3b904e11a3dece38e"},"P":{"status":"pass","command":"python3 -I gates.py","unmodified":true,"before_policy_changes":true,"readme_exact_6_decimals":true,"columns":["seed","perfect_info","gaussian_plain","gaussian_qm","lattice_qm"],"rows":[["10000","448.261189","443.455598","443.522608","443.663520"],["10001","576.779199","571.463409","571.623551","571.977293"],["10002","531.886497","525.168028","525.865859","526.411631"]],"gates_sha256":"603280c1f595ca163ffaf2ba1ebdc7945fdb08dabae67fc53c922d39e1cce604"},"variant":{"name":"RUN SCALE","built":true,"selected":{"enabled":false},"best_live_setting":{"weight":4096,"warmup":512},"volatility":"At first callbacks t>=1 with tell label pos, lp is the existing arb log-price reading. S accumulates squared log-price differences between consecutive such pins; D accumulates their elapsed step gaps. sigma2=(weight*(0.000945)^2+S)/(weight+D). No oracle drift correction or clipping.","rate":"Count first callbacks dt>=1 weighted by 1-pi after LEAN tell update and retail-floor cap. R=sum(1-pi); rho=(weight*0.26+R)/(weight+t). This is an effective own retail-first arrival intensity for the likelihood, not an estimate of the unobserved total market Poisson rate.","application":"Use prior sigma2 and rho until t>=warmup. Accumulate from the start, update estimates after the current posterior, and apply from the next first callback. sigma2 replaces each SIG2 propagation increment; rho replaces 0.26 in L_ret. Tell, tables, fees and rival tracking are unchanged. enabled=False leaves both at priors exactly.","settings_units":{"weight":"prior pseudo-steps, shared by variance and rate","warmup":"elapsed run steps"},"settings_predeclared_before_scoring":true,"selection_rule":"Maximum choose mean paired difference vs LEAN, including the zero-change control. All six live candidates were negative, so the control wins. A preliminary live-only selection manifest was corrected before any report seed was run; final hashes below govern the entire report."},"choose":{"seeds":[64000,64255],"n":256,"table":[{"setting":{"weight":256,"warmup":128},"n":256,"mean_diff":-0.02308370440830787,"se":0.010814359369973983},{"setting":{"weight":256,"warmup":512},"n":256,"mean_diff":-0.03675449895115346,"se":0.013453294826236275},{"setting":{"weight":1024,"warmup":128},"n":256,"mean_diff":-0.02888180196019441,"se":0.012745296937225743},{"setting":{"weight":1024,"warmup":512},"n":256,"mean_diff":-0.024691862200798997,"se":0.01140713031894942},{"setting":{"weight":4096,"warmup":128},"n":256,"mean_diff":-0.03659090065742898,"se":0.01502130211122943},{"setting":{"weight":4096,"warmup":512},"n":256,"mean_diff":-0.004138322470381706,"se":0.009558825110927037},{"setting":{"enabled":false},"n":256,"mean_diff":0.0,"se":0.0}],"control_edges_exact":true,"report_seeds_not_used":true},"frozen":{"time_unix":1794300280.5765738,"sha256":{"experiment.py":"c4661c378293734205f58bd706e0de99021f152e77db1e919cfcad6b0284c451","check_scale.py":"f4a29ae91c13ada51b4e0c9ec3fa9ea5cc0c037c5a83d17508f705cadb76fe8b","README-scale.md":"8a848103e4559a3c61abbfc9e7fe8c9dd4fb8340db4d8eeea60135d81b835818","settings.json":"9fb480bcf4fac8ff4504d5ea37d587ced9e56ba7c169d72745211dcd696cf041","ref/scale.py":"2aae826f93d374fbe0235d968e5e0ce5deba763dab06027b267ac4e7c81841d8","ref/policy.py":"962135885c1ad1ef142ed4b364870869e61948982c165ca2426ee864c1f10b51","ref/lean_tell.py":"b70054f8c0561779e40c4c8df3f41ab08da05b9aef591816ac6c9034beb40a95","ref/port.py":"81ec1136146777e10056c3a1e1ad5282de5a1b53e90d425decefc288e5948aac","ref/twocomp.py":"9d3c1833321493fb51bbde4e1b4dabc2f8978bd6d774ee2af8dc8aed13f0f0af","ref/qmref.py":"1dfc9b7a3c2237ff7a93dd9f0af54b9bdab16f2ce0a7eb00784cb4432598db92","ref/blob.bin":"3ac7cb8811ecfb6a17f499aa4e9b70dd55f7fb6432b3aec3b904e11a3dece38e"},"report_not_yet_run_at_freeze":true,"hashes_rechecked_every_report_block":true},"report":{"seeds":[10512,11023],"steps_per_seed":10000,"order":"ascending seeds, pick then LEAN then qt1 for each seed","each_arm_once":true,"paired_vs_LEAN":{"n":512,"mean_diff":0.0,"se":0.0,"min":0.0,"worst5":[{"seed":10512,"diff":0.0},{"seed":10513,"diff":0.0},{"seed":10514,"diff":0.0},{"seed":10515,"diff":0.0},{"seed":10516,"diff":0.0}]},"paired_vs_qt1":{"n":512,"mean_diff":3.158035559402719,"se":0.04351541480762935,"min":0.225518981451728,"worst5":[{"seed":10642,"diff":0.225518981451728},{"seed":10519,"diff":0.4145174142894348},{"seed":10731,"diff":0.4861750638468152},{"seed":10822,"diff":0.6628634339496102},{"seed":10838,"diff":0.9434240850990818}]},"mean_edge":{"pick":531.8087581086368,"lean":531.8087581086368,"qt1":528.650722549234},"replica_not_board_scores":true},"belief_error":{"metric":"abs(m - ln(true_price))*10000 after each own callback","weighting":"pooled callbacks, not equal-weighted seed means","pin":"tell-positive first callback at t>=1, irrespective of hidden arb flag; never means no pin yet","truth_access":"evaluation wrapper only; policy receives original public arguments","by_steps_since_pin":{"columns":["steps_since_pin","LEAN_n","LEAN_mae_bps","pick_n","pick_mae_bps"],"rows":[["never",2086,9.954576241632227,2086,9.954576241632227],["0",3222645,0.04761678469963403,3222645,0.04761678469963403],["1",527202,5.413544511632413,527202,5.413544511632413],["2",376897,7.740729683860913,376897,7.740729683860913],["3",289795,9.063443698034755,289795,9.063443698034755],["4",228075,9.820612176460532,228075,9.820612176460532],["5",182474,10.250118465128024,182474,10.250118465128024],["6",145102,10.44102603099438,145102,10.44102603099438],["7",115518,10.562033765380166,115518,10.562033765380166],["8",92335,10.602827499451793,92335,10.602827499451793],["9",73614,10.656548841381543,73614,10.656548841381543],["10",58953,10.679893690390127,58953,10.679893690390127],["11",47087,10.704041111105932,47087,10.704041111105932],["12",37455,10.709632831469987,37455,10.709632831469987],["13",29898,10.705440129598275,29898,10.705440129598275],["14",23477,10.593884204165583,23477,10.593884204165583],["15",18860,10.656459646368655,18860,10.656459646368655],["16",15190,10.602740701098739,15190,10.602740701098739],["17",12178,10.551151647036964,12178,10.551151647036964],["18",9636,10.575685658116296,9636,10.575685658116296],["19",7731,10.589209635620728,7731,10.589209635620728],["20",6062,10.77685297971534,6062,10.77685297971534],["21",4996,10.75872953656014,4996,10.75872953656014],["22",3880,10.790800880100244,3880,10.790800880100244],["23",3044,10.531135479047268,3044,10.531135479047268],["24",2487,10.593649475592185,2487,10.593649475592185],["25",1988,10.351304418210866,1988,10.351304418210866],["26",1597,10.30725458516983,1597,10.30725458516983],["27",1235,10.330144289725908,1235,10.330144289725908],["28",1044,11.079905604602585,1044,11.079905604602585],["29",782,10.60726970430411,782,10.60726970430411],["30",638,10.858220885942565,638,10.858220885942565],["31",467,10.357366774902282,467,10.357366774902282],["32",423,10.46879525201309,423,10.46879525201309],["33",329,10.797232447130195,329,10.797232447130195],["34",242,10.977869515851172,242,10.977869515851172],["35",200,9.781173902988844,200,9.781173902988844],["36",181,11.438005384227896,181,11.438005384227896],["37",117,10.540074119024101,117,10.540074119024101],["38",113,11.326029280691067,113,11.326029280691067],["39",103,11.78108618782741,103,11.78108618782741],["40",50,10.55244321704727,50,10.55244321704727],["41",53,10.919589739174823,53,10.919589739174823],["42",53,12.20944179533969,53,12.20944179533969],["43",39,10.875644844590083,39,10.875644844590083],["44",25,10.96455881713396,25,10.96455881713396],["45",28,13.571045169558728,28,13.571045169558728],["46",27,10.627343491743453,27,10.627343491743453],["47",19,13.312103549811473,19,13.312103549811473],["48",9,15.110518483327537,9,15.110518483327537],["49",9,12.009186508101047,9,12.009186508101047],["50",13,10.69500613872343,13,10.69500613872343],["51",10,12.00415644529329,10,12.00415644529329],["52",2,17.479128854391845,2,17.479128854391845],["53",5,14.397063431466961,5,14.397063431466961],["54",3,7.14228060022748,3,7.14228060022748],["55",7,13.218730153552778,7,13.218730153552778],["56",3,9.304708000733205,3,9.304708000733205],["57",2,20.264806216347964,2,20.264806216347964],["58",3,14.840504508881006,3,14.840504508881006],["59",6,17.598361908001497,6,17.598361908001497],["62",3,13.164949790755998,3,13.164949790755998],["63",2,15.80438487230218,2,15.80438487230218],["64",2,8.332633243965937,2,8.332633243965937],["66",3,3.2085241971380185,3,3.2085241971380185],["67",1,5.316024437407307,1,5.316024437407307],["68",1,4.5600118444877324,1,4.5600118444877324],["69",1,4.523492618142555,1,4.523492618142555],["71",1,0.5944040842376097,1,0.5944040842376097],["73",1,5.961070457356499,1,5.961070457356499],["74",2,3.7920503699950814,2,3.7920503699950814],["91",1,119.35740820963048,1,119.35740820963048],["114",1,51.9401480697379,1,51.9401480697379],["118",1,19.564898182959922,1,19.564898182959922],["128",1,52.06634047415726,1,52.06634047415726],["132",1,37.93277850159704,1,37.93277850159704],["134",1,35.35150695354261,1,35.35150695354261],["139",1,8.342326218260254,1,8.342326218260254]]}},"observables_check":{"status":"pass","seeds":[64000,64003],"settings":6,"callbacks":247985,"comparison":"exact Python float fee pairs on every callback; therefore fee wads also equal","replaced":["init sigma","init rate","init size","hidden execution path","hidden previous-reserve tuple (unused)","true arb flag","true price","true rival spot","hidden phase"],"garbage":"raising sentinels; normal twin receives real init parameters, hidden path/flag, current true price and actual rival spot","simulator_market_not_poisoned":true,"details_in_bundle":"scratch/evidence/checks.json"},"control_check":{"control":[{"seed":64000,"control_callbacks":9512},{"seed":64001,"control_callbacks":10767},{"seed":64002,"control_callbacks":10492},{"seed":64003,"control_callbacks":10562}],"estimator_settings":[{"weight":256,"warmup":128},{"weight":256,"warmup":512},{"weight":1024,"warmup":128},{"weight":1024,"warmup":512},{"weight":4096,"warmup":128},{"weight":4096,"warmup":512}],"pass":true},"contract_cost":{"implemented":false,"scope":"replica-only item; no Solidity, F gate, engine or gas claims","extra_state":"Last pin timestamp and log reading; cumulative squared move S and elapsed pin steps D; weighted first-retail count R; cached sigma2 and rho; optional raw first-callback count. Eight scalar state values including optional count; settings can be constants.","extra_arithmetic":"On each first callback: one subtraction/addition for 1-pi and count. On a positive pin: one log-price difference, square and two accumulator additions; lp already exists. After warmup: two weighted sums and two divisions. Reuse cached sigma2/rho in original filter. No extra loops or table accesses. Selected disabled control needs none of this additional state."},"timing":{"first_run":{"seed":64000,"lean":439.32557072475703,"control":439.32557072475703,"values":[439.2369425455008,439.2008805611108,439.2374439286854,439.3444290309898,439.30000618056243,439.28237556823234],"seconds":3.9706850121729076},"choose_summed_seconds":797.0417835041881,"report_summed_seconds":534.4774468191899,"command_limit_seconds":480,"subprocess_timeout_seconds":450,"cuts":"None: all six settings, all 256 choose seeds and all 512 report seeds completed. No contracts by item scope.","report_blocks":[[10512,10639],[10640,10767],[10768,10895],[10896,11023]]},"limitations":["No live setting has a report-block estimate: the maximum-mean rule selected the disabled control. Its zero vs LEAN and zero SE are an identity, not evidence that the live estimators have zero effect.","Best live choose difference is -0.004138322470381706, SE 0.009558825110927037; this is selected in-sample, not an unbiased report estimate.","Tell-positive pins can be false positives and pin times are endogenous; squared displacement per elapsed step is not guaranteed to be an unbiased diffusion estimate.","Weighted first-callback rate depends on the existing classifier and cannot count orders routed solely to the rival.","No board-score, deployment, gas or real-engine claim. Local checks are reproducible measurements, not independent certification.","Per-seed choose edges omitted from bundle to meet 64000-byte cap; the full choose table, log hash and executable reproduction harness are supplied."],"conclusion":"No RUN SCALE setting beat LEAN on the prescribed choose block. Keep LEAN. The selected zero-change control reproduces LEAN on the full report block.","evidence_sha256":{"choose.jsonl":"934740c34e5fd13dc4f479b17ba5b83887164b1936eeefc5841e1b4950ef2817","scale_report.jsonl":"bb97bc64778efbf44a3ca37724ac1e5dfb608a9b76ef7fde795a69824db0fcf8","poison.json":"75a7575825f2c9fba59e29cd794d705521909d6abc4207359dc76985f866336e","scale_checks.json":"2f2fcb06773e6c8080ebc3b82103b48fa78a7445b0adf36cc279a7b8ab0a5966","scale_frozen.json":"e46d223046cdd5882f3ccf68d2bea14a6fff69e096fda6fccbbc86e35a8d4672"},"provenance":{"replica_gate":"https://raw.githubusercontent.com/gtmcknight/amm-sim/4812a6382311624e1506aca131ca35c378f930d9/research/solved/README.md","TCA":"https://api.imdnotdead.fun/artifacts/dc359635b5851de9f5b3ecf81dc2107d46acd5dbe67e0be234bcfbe0c8a488e7","LB4":"https://api.imdnotdead.fun/artifacts/93cc15561f172c49c8bce174143333ede904fdbfcf51276cbbeb514d4f5b614e","new_measurements":"Bundled scratch/experiment.py and scratch/check_scale.py; supplied frozen hashes, per-seed report edges and check records. These are local measurements, not claims copied from the input 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","file_sha256":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