{"item":"bs-b","status":"incomplete","credit":"Taylor (gtmcknight), amm-sim/research/solved @4812a6382311624e1506aca131ca35c378f930d9: replica, Gaussian filter, DP, qmdp and qm tables. COMBO and TC artifact authors: two-component and branch-offset extensions.","summary":"Reproduced Gate P, verified all inputs, collected observable COMBO callback transitions and completed fresh paired COMBO-vs-qt1 baselines. The requested belief-state DP extension, saved-value solve, qmdp-generated candidate and collapsed-axis solve were NOT implemented. This is reusable measurement work, not a solved policy or a gain claim.","gates_output":"seed   perfect-info      gaussian+plain    gaussian+qm       lattice+qm\n10000  448.261189  443.455598  443.522608  443.663520\n10001  576.779199  571.463409  571.623551  571.977293\n10002  531.886497  525.168028  525.865859  526.411631\n","reference_checks_output":"QMRef 10000 443.101741\nQMRef 10001 571.454483\nQMRef 10002 525.908441\nCombo 10000 444.195330\nCombo 10001 572.172682\nCombo 10002 526.274760\n","gates":{"P":{"status":"pass","readme_values_matching_6dp":12,"qt1_values_matching_6dp":3,"combo_values_matching_6dp":3,"gates_py_unmodified":true},"Q":{"status":"partial_COMBO_only_no_candidate","fixed_callback_nonleak":{"seeds":[64000,64063],"callbacks":692152,"bit_identical":true,"randomized":"arb,p,s2,j at every callback; sigma,lam,size at init; actual observable callback sequence held fixed"},"additional_checks":["All 64 instrumented census edges bit-equal independently run unchanged COMBO edges.","AST check: no arb,p,s2,j parameter reads in on_trade of COMBO, TwoComp or QMRef.","All 692152 transition counts accounted for; each conditional probability row sums to one within 1e-12."],"does_not_establish":"No new candidate exists; this does not pass candidate observability, candidate pairing or the collapsed-axis control."},"F":{"status":"not_applicable_replica_only"}},"hashes":{"git_rev_parse_HEAD":"4812a6382311624e1506aca131ca35c378f930d9","artifacts":{"qt1":{"url":"https://api.imdnotdead.fun/artifacts/8a6e303b662e1a5ea9bb47f31acedd3988ef65b3ddb66d074517aa59ad41ca40","sha256":"8a6e303b662e1a5ea9bb47f31acedd3988ef65b3ddb66d074517aa59ad41ca40","verified":true},"TC":{"url":"https://api.imdnotdead.fun/artifacts/d3c849db2ac31e567b57e52b80b86e8c24c842e5b4125b9d75c78e3cb07115b9","sha256":"d3c849db2ac31e567b57e52b80b86e8c24c842e5b4125b9d75c78e3cb07115b9","verified":true},"COMBO":{"url":"https://api.imdnotdead.fun/artifacts/d360bea6c8c982717b7b43a8069a87013169c89ee3e4da25622db4d880b936d4","sha256":"d360bea6c8c982717b7b43a8069a87013169c89ee3e4da25622db4d880b936d4","verified":true},"QMS1":{"url":"https://api.imdnotdead.fun/artifacts/17d249ab0c33fc44931d9b105cf3f9e3846a560bd518b67310c2a56defacdecc","sha256":"17d249ab0c33fc44931d9b105cf3f9e3846a560bd518b67310c2a56defacdecc","verified":true}},"files":{"blob.bin":"3ac7cb8811ecfb6a17f499aa4e9b70dd55f7fb6432b3aec3b904e11a3dece38e","qmref.py":"1dfc9b7a3c2237ff7a93dd9f0af54b9bdab16f2ce0a7eb00784cb4432598db92","twocomp.py":"9d3c1833321493fb51bbde4e1b4dabc2f8978bd6d774ee2af8dc8aed13f0f0af","combo.py":"c5b711a0b4fb4783e8879a484bf87a427171f4a11aa5eb5ec3513c24ead1a796","collect.py":"abb6b85da5f3765da05230e2d418f51d028d5cb14913a840d0533460cc2c6d38","baselines.py":"76b2e096a07c7b0acf12b413be4dc2dacd6539386e0446b4b7c806b3285886f8","combo_observed.py":"b6258d369bf8511b1a9924617d90482b187d32f3ed43cce6dd5510bfd8d834cd"},"pinned_solved_files":{"README.md":"02d2b51f17adbb5411a2a67f7a37255143ba381a73ff10abba557d7d23c0cef2","gates.py":"603280c1f595ca163ffaf2ba1ebdc7945fdb08dabae67fc53c922d39e1cce604","dp.py":"ca4e7c378d23c46c7def4716611135c471a831d15234b984fe30d58d9eec5734","qmdp.py":"63b8c35048718c37eb0a5dae9e70849fa3af257c335e4a2e3a625c833f1dc1eb","replica2.py":"6e37b4e61e1ffa5ffb1e43912ddb8659105989aa986eb48fcd1d7608f8dca685"}},"frozen_spec":{"candidate":null,"candidate_code_sha256":null,"candidate_params_sha256":null,"policy_selection":"None. No learned or solved policy was selected; report results only score unchanged COMBO against qt1.","baseline_code_sha256":"76b2e096a07c7b0acf12b413be4dc2dacd6539386e0446b4b7c806b3285886f8","transition_collector_sha256":"abb6b85da5f3765da05230e2d418f51d028d5cb14913a840d0533460cc2c6d38","training_seeds":[64000,64063],"choose_seeds":[64000,65023],"report_seeds":[10000,12047],"replica_call":"replica2.run(seed, policy), default n_steps=10000, cfg=None, qcap=None","no_report_tuning":true,"report_execution":"Each policy once per seed in the paired baseline screen; the separate required 3-seed Gate P checks preceded it."},"choose":{"seeds":[64000,65023],"C-COMBO":{"n":0,"mean_diff":null,"se":null,"worst5":[],"wins":null,"sum_d":null,"sum_d2":null,"status":"not_run_no_candidate"},"C-qt1":{"n":0,"mean_diff":null,"se":null,"worst5":[],"wins":null,"sum_d":null,"sum_d2":null,"status":"not_run_no_candidate"},"COMBO-qt1":{"n":1024,"mean_diff":0.6096046465295315,"se":0.01940052280944413,"worst5":[[64101,-2.7769830832371554],[64845,-1.1638684799705743],[64374,-1.023433823667915],[64795,-0.9831714544297938],[64555,-0.9461893679592208]],"wins":875,"sum_d":624.2351580462403,"sum_d2":774.8145734774697}},"report":{"seeds":[10000,12047],"C-COMBO":{"n":0,"mean_diff":null,"se":null,"worst5":[],"wins":null,"sum_d":null,"sum_d2":null,"status":"not_run_no_candidate"},"C-qt1":{"n":0,"mean_diff":null,"se":null,"worst5":[],"wins":null,"sum_d":null,"sum_d2":null,"status":"not_run_no_candidate"},"COMBO-qt1":{"n":2048,"mean_diff":0.5973909633856562,"se":0.013387993974623986,"worst5":[[10146,-3.552496929485528],[11062,-2.3348491437070606],[11808,-1.8227381435300458],[10519,-1.782691465320454],[11376,-1.7502956875490554]],"wins":1753,"sum_d":1223.456693013824,"sum_d2":1482.2951576559892}},"solve":{"state_size":null,"sweeps":0,"convergence_span":null,"solve_wall_seconds":0,"kappa_requested":1e-05,"kappa_used":null,"saved_values":null,"tables":null,"status":"not_implemented","control_comparison":{"status":"not_run","reproduces_COMBO_within_se":null,"paired":{"n":0,"mean_diff":null,"se":null,"worst5":[],"wins":null,"sum_d":null,"sum_d2":null,"status":"not_run_no_candidate"}},"prospective_decision_states_at_original_grid":427572,"prospective_count_explanation":"Taylor decision grid: 321 own rows times (13 phase-0 rival columns +49 phase-1 +49 phase-2), times 4 sd and 3 pi levels. This is only dimension arithmetic, not an allocated or solved state."},"transition_counts":{"status":"callback_census_complete_intermediate_silent_updates_missing","callbacks":692152,"sd_quartiles_bps":[5.5002823683146245,11.69529113949514,17.046391399866827],"zero_sd_quotes":30323,"sd_intervals":"bisect_right(quartiles, sd), including all zeros; duplicate cuts retained","pi_rule":"COMBO local pi on first own trades; zero on subsequent same-step callbacks (arb cannot occur there). Initial retained pi=0.","fill_rule":"absolute log(post_spot/previous_own_spot)*10000, bucketed by bisect_right([5,10,20,40], fill); own fill impact, not hidden total order size","transition_definition":"previous callback quote belief/phase -> current quote belief/phase, conditioned on current observable fill bucket; one count per own callback, initial state (sd=0,pi=0,phase=0). Silent intermediate truncation updates are NOT separately counted.","observed_condition_rows":95,"possible_condition_rows":180,"nonzero_entries":987,"mean_pi_by_sd_pi_level":[[0,0,63436,6.189124431487264e-07],[0,2,109602,0.9645931392021905],[1,0,96097,0.0007126332971940031],[1,1,13829,0.6775355236983586],[1,2,63111,0.8719264501143885],[2,0,112245,0.01517116283812663],[2,1,48504,0.5583466473206207],[2,2,12289,0.8242598351603727],[3,0,107157,0.06447545004326789],[3,1,63089,0.4380610894465899],[3,2,2793,0.8094085702892068]],"occupancy_sd_pi_phase":[[0,0,1,47274],[0,0,2,16162],[0,2,0,109602],[1,0,1,68651],[1,0,2,27446],[1,1,0,13661],[1,1,1,168],[1,2,0,63111],[2,0,1,74009],[2,0,2,38236],[2,1,0,32808],[2,1,1,15696],[2,2,0,12289],[3,0,1,58241],[3,0,2,48916],[3,1,0,20403],[3,1,1,42686],[3,2,0,2793]],"full_counts_and_probabilities":"Bundled scratch/census.json -> transitions. before=[sdLevel,piLevel,phase,fillBucket], after rows=[sdLevel,piLevel,phase,count,probability].","unvisited_sd_pi_cells":[[0,1]],"unvisited_row_handling":"No smoothing or fallback selected; no solver consumed the matrix.","reward_weighting":"Level means measured but not incorporated into a reward or policy.","wall_seconds_collection_plus_nonleak":117.93290622299537},"findings":[{"claim":"Gate P reproduced and all four artifact byte hashes plus both COMBO-published extracted-source hashes match.","evidence":["gates_output","reference_checks_output","hashes"],"sources":["https://raw.githubusercontent.com/gtmcknight/amm-sim/4812a6382311624e1506aca131ca35c378f930d9/research/solved/README.md","https://api.imdnotdead.fun/artifacts/d360bea6c8c982717b7b43a8069a87013169c89ee3e4da25622db4d880b936d4"]},{"claim":"Observable sd/pi/phase callback transitions and per-cell mean pi are available for reuse. The sd=level0, pi=middle cell had no quote observations.","evidence":["transition_counts","source_bundle: scratch/census.json"],"sources":["https://api.imdnotdead.fun/artifacts/d360bea6c8c982717b7b43a8069a87013169c89ee3e4da25622db4d880b936d4"]},{"claim":"The existing dp.py and qmdp.py numerical implementations import numpy and numba; they are not stdlib-only. No replacement numerical pipeline was completed here.","sources":["https://raw.githubusercontent.com/gtmcknight/amm-sim/4812a6382311624e1506aca131ca35c378f930d9/research/solved/dp.py","https://raw.githubusercontent.com/gtmcknight/amm-sim/4812a6382311624e1506aca131ca35c378f930d9/research/solved/qmdp.py"]}],"limitations":["The central requested solver implementation and experiment remain incomplete; no score improvement, converged values or learned policy is claimed.","No relative value iteration sweeps, qmdp tables at kappa=1e-5, extended COMBO lookup, or collapsed-axis solve/control comparison.","C-COMBO and C-qt1 have zero coverage on both windows. Baseline COMBO-qt1 statistics are NOT candidate statistics.","The census records before/after each own callback, not every intermediate filter update during silent steps; it therefore does not meet that portion of the requested transition coverage.","Pi on later same-step trades is defined as zero, not the stale first-trade posterior. The fill buckets are declared measurement conventions, not a fitted action-dependent transition model.","Conditional transitions are measured under unchanged COMBO only; action-dependent counterfactual transitions and unvisited-cell handling remain unverified.","No contracts, engine seeds, engine scoring, Gate F, gas or deployment work. Replica edges are not board scores."],"source_bundle":{"format":"base64(zlib(UTF-8 JSON 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"},"regeneration_commands":["Credit Taylor (gtmcknight). Unpack source_bundle into a fresh test/scratch/bs-b/; verify compressed/uncompressed and per-file SHA256s first.","python3 -I test/scratch/bs-b/scratch/prepare.py","python3 -I test/scratch/bs-b/scratch/spot.py","python3 -I test/scratch/bs-b/scratch/collect.py","python3 -I test/scratch/bs-b/scratch/baselines.py 64000 65024","python3 -I test/scratch/bs-b/scratch/baselines.py 10000 12048","python3 -I test/scratch/bs-b/scratch/summarize.py","For slower runs, invoke baselines.py on consecutive <=128-seed subranges instead. It resumes from scratch/baselines.jsonl and skips completed seeds. Do not use report data to select a candidate."],"local_validation":{"all_paired_baseline_seeds_unique_and_complete":true,"census_counts_probabilities_checked":true,"instrumented_census_equals_unchanged_combo_64_seeds":true,"source_bundle_roundtrip_checked":true,"independent_authority":false}}