{"key":"values-1","track":"B","status":"candidate_gate_failed_base_retained","mechanism":{"proposal":"Average held-action passive VN values over the full price posterior and branch-conditioned phase/rival state, maximize once, then use original parabolic refinement and exponential fee conversion. Do not average optimal fees or decision values VD.","candidate":{"policy":"valuepolicy:ValuePolicy","alpha":1.0,"thr":0.9,"kappa":1e-05,"grid":"unchanged dp.py, AMINL=-12, NA=43, 5 bps","rival":"arb: price-conditional band clip; retail: band clip then observed side router min/max; subsequent same-step calls advance each branch separately","belief_update":"unchanged ThrLattice; delegation plus observational cut/pin/deposit hooks","candidate_settings_endpoint_tested":1,"candidate_settings_performance_scored":0},"cause_of_rejection":"Grid endpoints are exact, but off-grid delta-price interpolation of values before argmax/refinement is not equivalent to the original lookup interpolation of refined offsets. The maximum observed fee discrepancy is 6.90900264632921 bps, exceeding 0.01. This is not explained by genuine zero-fee duplicate actions.","scope":"One experimental mechanism; no engine work or entry submission."},"frozen_settings":{"policy":"valuepolicy:ValuePolicy","alpha":0.0,"thr":0.9,"qm":"qm_k1e-5.json","reason":"candidate rejected before performance scoring: off-grid delta-price endpoint maximum fee difference 6.90900264632921 bps > 0.01","candidate_settings_performance_scored":0,"candidate_settings_endpoint_tested":1,"selection":"mandated unchanged-base fallback; no performance-based tuning","before_confirmation_and_holdout":true,"source_sha256":{"valuepolicy.py":"afd5a588e3c72bd6480fcb8e2761848ba9f2eeb4c7daf798328c2a3da6306f61","actionvalues.py":"ec0059746402861696b660998a22f24c4e49d5320faa39208b75f1d0c3ac0d57","thrpol.py":"663965707d4f20f81ab0ade8ed510742a330605fd9e889d426db1d920abc8958"}},"solver":{"implementation":"pinned dp.py solve through regenerate.py","DP_SAVEVN":1,"DP_STATE":"scratch/dpstate.npz","bounded_sweeps":[10,30,30,30,20],"total_sweeps":110,"convergence_tolerance":2e-07,"last_max_value_change_approx":1.88e-07,"gain_midpoint":536.8206098114671,"value_precision":"float64, saved directly from solve; original DP_SAVEVN main casts float32","command_timeout_seconds":465,"value_arrays_delivered":false},"checks":{"grid_delta_endpoints":[{"phase":0,"kappa":0.0,"n":143,"max_value_error":0.0,"max_fee_error_bps":0.0},{"phase":0,"kappa":1e-05,"n":143,"max_value_error":0.0,"max_fee_error_bps":0.0},{"phase":1,"kappa":0.0,"n":99,"max_value_error":0.0,"max_fee_error_bps":0.0},{"phase":1,"kappa":1e-05,"n":99,"max_value_error":0.0,"max_fee_error_bps":0.0},{"phase":2,"kappa":0.0,"n":99,"max_value_error":0.0,"max_fee_error_bps":0.0},{"phase":2,"kappa":1e-05,"n":99,"max_value_error":0.0,"max_fee_error_bps":0.0}],"grid_pass":true,"non_tie_argmax_mismatches":0,"offgrid_delta_endpoints":{"n":120,"worst":{"max_fee_error_bps":6.90900264632921,"phase":1,"w_bps":-102.0,"rival_bps":1.75,"candidate_fees_bps":[0.0,88.9595030462531],"original_lookup_fees_bps":[0.0,95.86850569258232],"argmax":[9,0],"top2_value_gap":0.0},"pass":false,"interpretation":"The original qmdp lookup interpolates refined offsets. The new kernel interpolates action values before refinement. These operations need not commute. A nonzero error is not excused as a tie."},"forced_pi_0_1_policy_endpoints":{"n":36,"pi":[0,1],"branch_state_pass":true,"max_fee_error_bps":0.004941604571095937,"pass":true},"ties":{"delta_case":{"phase":1,"w_bps":-102.0,"rival_bps":1.75},"argmax_index_pairs_within_1e_14":33,"distinct_effective_grid_action_pairs":1,"effective_offsets_bps":[[-15,102.0]],"explanation":"All tied index pairs here represent the same effective grid quotes: negative bid fees clamp to zero. They do not explain the 6.909 bps difference in the ask fee after value interpolation versus optimal-offset interpolation."},"all_required_endpoint_checks_pass":false,"zero_change_equivalence":{"seeds":[63000,63003],"callbacks":41329,"max_fee_diff_bps":0,"exact_full_belief_state":true},"hidden_input_independence":{"callbacks":41329,"mutations":["arb inverted","p x1.1","s2 x0.8","j +100","init sigma/lam/size x2"],"max_fee_diff_bps":0,"interface":"(self, is_buy, ax, ay, t, x, y)","needs_flag":false},"active_experiment_replay":{"tuning_seed":63000,"replayed_callbacks":48,"max_accelerator_fee_error_bps":0.0,"max_hidden_mutation_fee_error_bps":0.0,"belief_state_exact":true,"standard_library_npy_max_error":0.0,"scoring":false},"diffusion_acceleration":{"seeds":[63000,63019],"n":20,"callbacks":210961,"active_acceleration":true,"max_fee_difference_bps":0,"full_belief_and_state_bit_exact":true,"four_arms":["ThrLattice","ValuePolicy(alpha=0)","FastBase","FastValue(alpha=0)"],"fastmath":false,"scope":"diffuse only; original thrpol.py, run.py and pair.py unmodified"},"standard_library_active_fallback":{"callbacks":8,"max_fee_error_bps":0.0,"all_recorded_outputs_exact":true,"seed":63000},"original_gates":{"seeds":[10000,10001,10002],"four_reference_arms":"published values reproduced to all six printed decimals","purpose":"predeclared harness calibration only, not candidate scoring/tuning"},"pinned_input_checksums_unchanged":26,"frozen_policy_source_hashes_unchanged":3,"run_py_unchanged":true,"pair_py_unchanged":true,"needs_flag":false,"hidden_labels_used_offline_for_training":false,"validation_authority":"Local checks only; no independent behavioral certification."},"tuning":{"paired_vs_fresh_base":{"n":256,"mean_diff":0.0,"se":0.0,"sum":0.0,"sumsq":0.0,"worst5":[[63000,0.0],[63001,0.0],[63002,0.0],[63003,0.0],[63004,0.0]]},"retained_policy":{"n":256,"first_trades":1800460,"misread_count":520809,"first_trade_misread":0.28926441020628063,"callbacks":2803968,"callback_price_sse_bps2":487962272.3517345,"callback_price_rms_bps":13.191877082504835,"mean_edge":527.1685303252768,"rows_sha256":"6f2b3758c0026e0bb1c5ee374430cebdc2cf21dd39f781b0475c2aa8484a44a2"},"unchanged_base":{"n":256,"first_trades":1800460,"misread_count":520809,"first_trade_misread":0.28926441020628063,"callbacks":2803968,"callback_price_sse_bps2":487962272.3517345,"callback_price_rms_bps":13.191877082504835,"mean_edge":527.1685303252768,"rows_sha256":"6f2b3758c0026e0bb1c5ee374430cebdc2cf21dd39f781b0475c2aa8484a44a2"}},"selection":{"rule":"User-mandated base retention after failed endpoint check; no candidate performance score examined. alpha=0 was frozen before confirmation and holdout. There was no reward-based parameter selection.","candidate_performance_n":0},"confirmation":{"paired_vs_fresh_base":{"n":256,"mean_diff":0.0,"se":0.0,"sum":0.0,"sumsq":0.0,"worst5":[[63256,0.0],[63257,0.0],[63258,0.0],[63259,0.0],[63260,0.0]]},"retained_policy":{"n":256,"first_trades":1806420,"misread_count":523080,"first_trade_misread":0.28956721028332283,"callbacks":2820614,"callback_price_sse_bps2":496770677.3639629,"callback_price_rms_bps":13.271076356252479,"mean_edge":529.1539565729261,"rows_sha256":"e5f34ae3b991936971c0fa2c473834ae0a58cce8bf90a3b1af070d22eb4dafb1"},"unchanged_base":{"n":256,"first_trades":1806420,"misread_count":523080,"first_trade_misread":0.28956721028332283,"callbacks":2820614,"callback_price_sse_bps2":496770677.3639629,"callback_price_rms_bps":13.271076356252479,"mean_edge":529.1539565729261,"rows_sha256":"e5f34ae3b991936971c0fa2c473834ae0a58cce8bf90a3b1af070d22eb4dafb1"}},"holdout":{"paired_vs_fresh_unchanged_base":{"n":2048,"mean_diff":0.0,"se":0.0,"sum":0.0,"sumsq":0.0,"worst5":[[10000,0.0],[10001,0.0],[10002,0.0],[10003,0.0],[10004,0.0]]},"paired_vs_ref_lattice_qm":{"n":2048,"mean_diff":0.3228919198104912,"se":0.01069159987528695,"sum":661.282651771886,"sumsq":692.7408990952625,"worst5":[[11487,-1.9115248303883163],[10942,-1.6076924222966227],[10982,-1.4457581244053017],[11380,-1.2365145499310302],[10990,-1.1504964526710637]]},"retained_policy":{"n":2048,"first_trades":14472181,"misread_count":4180058,"first_trade_misread":0.28883400504733875,"callbacks":22636622,"callback_price_sse_bps2":3990446776.5684752,"callback_price_rms_bps":13.277152756808208,"mean_edge":534.1438162939719,"rows_sha256":"2d74845c78c1c1c7a215f450b66f3ed75c19975c8e62b6ec93da5773443c009b"},"fresh_unchanged_base":{"n":2048,"first_trades":14472181,"misread_count":4180058,"first_trade_misread":0.28883400504733875,"callbacks":22636622,"callback_price_sse_bps2":3990446776.5684752,"callback_price_rms_bps":13.277152756808208,"mean_edge":534.1438162939719,"rows_sha256":"2d74845c78c1c1c7a215f450b66f3ed75c19975c8e62b6ec93da5773443c009b"},"reference_lattice_qm_on_completed_candidate_seeds":{"n":2048,"first_trades":14315685,"misread_count":2322695,"first_trade_misread":0.162248261260289,"callbacks":22263118,"callback_price_sse_bps2":4143769057.6884427,"callback_price_rms_bps":13.64283973652866,"mean_edge":533.8209243741613,"rows_sha256":"02e2e352ea83b848b2f40b4094ee8fafc5869f56aba0f3d759bd2b66323a8a3a"},"target_n_per_arm":2048,"complete":true,"interpretation":"The alpha=0 fallback is exactly the unchanged base. Its positive gap versus lattice is inherited, not new action-value gain. Invalid alpha=1 was not scored on holdout."},"incremental_cost":{"retained_alpha_0":{"additional_algorithmic_storage_slots":0,"additional_value_interpolation_operations":0,"note":"Only Python delegation/alpha dispatch; no Solidity implementation or measured gas."},"rejected_alpha_1":{"candidate_action_pairs":1849,"max_current_step_hypotheses":122,"multilinear_corners_per_hypothesis_action":16,"max_value_corner_terms_per_callback":3609248,"naive_additional_hypothesis_storage_slots":488,"storage_assumption":"4 uncompressed 256-bit fields per hypothesis: mass, log price, phase, rival spot; excludes temporary scalars and precomputed value data. Packing could reduce this.","gas_estimate":{"label":"illustrative naive direct-port estimate, NOT EVM measured","value_access_only_gas":10827744,"assumption":"3 gas per corner value access, no reuse; excludes interpolation arithmetic, value-table access implementation, memory expansion, information incentive, filter, and storage writes. This is a cost model, not a rigorous lower bound.","within_245000_budget":false}}},"promotion":{"bar_incremental_over_unchanged_base":0.3,"promote":false,"incremental_holdout_mean":0.0,"reason":"Endpoint gate failed; retained policy has no incremental gain. No engine, Solidity gas or leaderboard claim."},"limitations":["Requested repair remains incomplete: the off-grid delta-price <=0.01 bps endpoint requirement fails. Retention of the base is intentional, not a successful repair claim.","No tuning/confirmation/holdout performance measurement of the invalid experimental alpha=1 policy. Fallback measurements must not be reported as experimental gain.","Full joint rival uncertainty is not propagated across new-step boundaries; previous rival estimate is collapsed to the base scalar before current-step branch conditioning.","Experimental action integration uses the original moment-based kappa information incentive; that incentive itself is not recomputed from the full posterior.","Experimental branch price hypotheses are captured before the base lattice rebin; the estimator itself is unchanged, but action integration retains the exact arb point rather than its numerically rebinned representation.","Solver regeneration needs numpy/numba and pinned solved inputs. They are not vendored in this source-only artifact; no tables or traces are delivered. Retained scoring and experimental scalar callback fallback use standard Python once values exist.","No contract or measured gas result; naive VN integration is far beyond the contract budget."],"seed_ledger":{"engine_seeds_used":0,"tuning_allowed":[63000,63255],"confirmation_allowed":[63256,63511],"holdout_allowed":[10000,12047],"candidate_alpha_1_scoring_seeds":[],"replay_checks":[63000,63003],"public_harness_calibration":[10000,10001,10002],"holdout_candidate_completed":[[10000,12047]],"holdout_base_completed":[[10000,12047]],"holdout_seed_reuse":"No repeat performance scoring within an arm; per-seed baseline and fallback runs are independent calls on matched seeds."},"provenance":{"solved_url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/e65314f88de945f6d055bfc2aab01c482ab6570e/research/solved","base_artifact":"https://api.imdnotdead.fun/artifacts/c9d678abb0ed0ee3a31b13a8203b6ee993896db0b6a3875c5c4f52a369bf0434","base_file_sha256":"663965707d4f20f81ab0ade8ed510742a330605fd9e889d426db1d920abc8958","reference_lattice_file_sha256":"3971e970ebcfeb053b1d747045aed3dbad164ca43008b1985b62daaeb20d9e44","original_run_sha256":"54d19a9194ebedee8b947dfaaf8626b1e4ef6f7d1b5aa12e738ec01a5ce401ac","original_pair_sha256":"16497bc5d3b596102fb0c0d7b6bf331dc788ee04c42d537e41f0578115f631db","execution_aliases":{"retained_policy":"valuepolicy:ValuePolicy or callback-bit-exact fastdiffuse:FastValue","unchanged_base":"thrpol:ThrLattice or callback-bit-exact fastdiffuse:FastBase","scope":"Only diffuse loop acceleration, no fastmath; source base unchanged; parity checked before alias scoring"},"sources":"sources.json","numeric_evidence":"Own local executions of original run.py through Blind; summarize.py aggregates completed rows and computes sample-SE, sum, sumsq and row hashes. No rows imputed; source recipe included."},"code_zb64":"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","code_sha256":"ad57d7b50118e0fb0fd9c89966012aabadf0304670c3df4eb6b4c1e6eefb3969","code_encoding":"base64(zlib(uncompressed USTAR tar)); code_sha256 hashes the uncompressed tar","code_files":["thrpol.py","actionvalues.py","valuepolicy.py","prepare.py","regenerate.py","regenerate.sh","check_policy.py","check_active.py","check_plain.py","check_branches.py","check_endpoints.py","check_ties.py","summarize.py","make_result.py","REPRODUCE.md","fastdiffuse.py","check_diffusion.py"],"reproduction":"Unpack code_zb64, read REPRODUCE.md, run prepare.py to fetch checksum-pinned input code/tables. Run bounded resumable regenerate.py then the endpoint checks; alpha=1 must remain rejected. Score frozen alpha=0 via unchanged run.py and compare with original pair.py; summarize.py adds sum/sumsq and diagnostics."}