{"item":"retail-quotient-signal","status":"measured","research_base_url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/66604b3426d8e97a73e2c39940b9b4dece51cc73/research","experiment":"One WAD-visible retail router-quotient grid consistency signal; equality update to rival estimate on predicted retail only.","conclusion":{"integration_lead":false,"threshold_mean_gain":0.2,"engine_result":false,"text":"The quotient grid distinguishes likely split fills from full orders and can justify a two-sided rival spot update. It does not decode an independent rival price beyond the marginal-price identity. See measured paired holdout gain and uncertainty; no engine claim."},"code_zb64":"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","sha256":"ff9afbb71f1a030333cd9b8ce283a83d8e5d423fdae1726d1f3d480685744efb","code_encoding":"base64(zlib(UTF-8 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","bundle_sha256":"4af0547eb8e900a776c8492efd9d195fed4c2f741f086eafc6a39ca886d7ee8a","bundle_encoding":"base64(zlib(UTF-8 JSON relative-path-to-text map)); SHA256 hashes decoded JSON bytes","freeze":{"manifest_sha256":"2a3be2d69e2e4bcb6fe3f8ec4b229f13041b478d2a5b437fa328cc77d3370f85","source_sha256":"ff9afbb71f1a030333cd9b8ce283a83d8e5d423fdae1726d1f3d480685744efb","parameters":{"qm":"qm_k1e-5.json","ratio_ulp_radius":2,"soft":1,"weight":1.0},"timing":"Source and parameters frozen after tuning and numerical repairs, before any holdout execution."},"method":{"signal":"For an interior retail split, paid=fl(N/D), D=gamma+sqrt(Kown*gamma/(Krival*0.997))*0.997; N is a reserve-scale subtraction on a reserve-ulp grid. Forward-round candidate grid numerators and compare their handed WAD integers with paid_w.","interval":"Enumerate WAD-compatible previous own reserve doubles, reconstruct gamma from previous WAD fee, allow ratio candidates +/-2 binary64 ulps, test nearest numerator integer +/-1. Paid low bits are never read: float(paid_w)/1e18 only locates the numerator integer, and forward WAD equality decides.","effect":"Only predicted retail: replace rival log spot by the marginal-price equality candidate on a quotient hit, set synced, then use the unchanged table lookup. No hit retains the original one-sided update. Arbitrage classification, price filter, table files, fee limits and every unrelated mechanism stay as TellPolicy.","allowed_inputs":["afterSwap side/timestamp and amount/reserve WAD integers","previous own WAD reserves and returned clamped fees","known initial equal constant product and fixed rival fee"],"needs_flag":false,"forbidden_inputs_used":false,"limitations":["The +/-2-ulp ratio interval is empirically checked, not a formal all-states rounding bound.","Full orders can match by chance; a hit is not proof. The rival estimate can be moved incorrectly.","TellPolicy and the replica themselves continue their shipped floating-point operations; only the new feature and its equality candidate are reconstructed from WAD integers.","Scoring rows in the bundle project exact edges and first-trade counts; aggregate price-error diagnostics are supplied instead of per-seed volume/error rows.","Upstream immutable table/calibration inputs are not embedded; their exact hashes and fetch recipe are supplied. No package was installed."]},"tuning":{"seed_interval":[60000,60255],"baseline":"tellpol:TellPolicy soft=1 qm=qm_k1e-5.json","choices":[{"weight":1.0,"ratio_ulp_radius":2,"reason":"Single direct equality-update variant, not a broad sweep; retained regardless of whether gain reaches 0.2."}],"repairs":["A pre-freeze unit test showed small paid amounts have more than five WAD-compatible doubles. Replaced paid-preimage enumeration by nearest-numerator search plus forward WAD equality.","Moved quotient evaluation from all callbacks into the predicted-retail lookup branch. First three tuning rows were bit-identical; original and repaired full 256-row tuning outputs were bit-identical."],"measurements":{"paired":{"n":256,"mean_diff":0.12323001572156955,"se":0.0166118832389228,"sum":31.546884024721805,"sumsq":21.90184352879548,"worst5":[[60003,-0.7686721075194782],[60025,-0.6533570417975625],[60182,-0.6102854965832876],[60031,-0.46725987353397613],[60209,-0.4314677476995712]]},"candidate":{"n":256,"mean_edge":529.818402253455,"first_trades":1792394,"first_trade_misreads":424,"first_trade_misread_rate":0.00023655513240950372,"log_price_rms_bps":7.116758590049795,"log_price_squared_error_sum_bps2":140759243.79460594,"price_samples":2779153},"baseline":{"n":256,"mean_edge":529.6951722377335,"first_trades":1787620,"first_trade_misreads":406,"first_trade_misread_rate":0.00022711762007585504,"log_price_rms_bps":7.152233929899862,"log_price_squared_error_sum_bps2":141684219.93703997,"price_samples":2769734},"diagnostics":{"calls":2779153,"retail":1807394,"hits":1615849,"changed":38421,"denominator_count":9452291,"age_counts":[638601,261924,331477,337903,196090,41399],"hit_age_counts":[553695,237293,301617,307357,178236,37651],"correction_abs_bps":272040.60948447406,"max_correction_bps":92.09490141026247,"runs":256,"hit_rate_predicted_retail":0.8940214474541799,"changed_rate_predicted_retail":0.021257678181957007,"age_bins_steps":["0","1","2..3","4..7","8..15","16+"],"age_definition":"integer callback timestamp minus last predicted-arbitrage hard pin timestamp; initial timestamp 0","denominator_count_scope":"All callbacks before the equivalent retail-only evaluation optimization; other diagnostic counts are unchanged."}},"score_rows_embedded":false},"holdout":{"seed_interval":[10000,12047],"scored_once":true,"baseline_rerun":false,"retuned_after_holdout":false,"runner":"One score_once.py driver, 32 disjoint 64-seed calls to the unmodified run.py with soft=1 qm=qm_k1e-5.json. Each candidate holdout seed executes exactly once.","baseline_file":"tell_qm.json","baseline_sha256":"ad382c07e6c2b3a5a8055ea767e140b7461105f29dafee69b7c1766c90d0634f","measurements":{"paired":{"n":2048,"mean_diff":0.12285540499524492,"se":0.006284515958726821,"sum":251.6078694302616,"sumsq":196.48512783728222,"worst5":[[11696,-1.875730951060632],[11701,-1.69652171052212],[11413,-1.1451048876382401],[11022,-1.0567118168170282],[11763,-1.005355664072681]]},"candidate":{"n":2048,"mean_edge":536.6550630464546,"first_trades":14388583,"first_trade_misreads":3597,"first_trade_misread_rate":0.0002499898704410295,"log_price_rms_bps":7.115711815695286,"log_price_squared_error_sum_bps2":1131935023.0449595,"price_samples":22355521},"baseline":{"n":2048,"mean_edge":536.5322076414594,"first_trades":14350251,"first_trade_misreads":3420,"first_trade_misread_rate":0.0002383233575496345,"log_price_rms_bps":7.149446150401305,"log_price_squared_error_sum_bps2":1138900370.4973536,"price_samples":22281321},"diagnostics":{"calls":22355521,"retail":14567245,"hits":13022844,"changed":310025,"denominator_count":50896573,"age_counts":[5156330,2109127,2680709,2722205,1575732,323142],"hit_age_counts":[4471597,1910155,2439765,2475015,1432115,294197],"correction_abs_bps":2209002.066861937,"max_correction_bps":114.38619342510825,"runs":2048,"hit_rate_predicted_retail":0.8939812572658729,"changed_rate_predicted_retail":0.021282335815729057,"age_bins_steps":["0","1","2..3","4..7","8..15","16+"],"age_definition":"integer callback timestamp minus last predicted-arbitrage hard pin timestamp; initial timestamp 0","denominator_count_scope":"Predicted retail callbacks only."}},"baseline_rows_embedded":false},"numerical_checks":{"fetched_files":34,"hash_mismatches":0,"unit_tests_passed":2,"synthetic":{"generator_seed":99181,"draws":30000,"interior":2086,"interior_hits":2086,"full":13823,"full_hits":831,"interior_detection_rate":1.0,"full_false_hit_rate":0.060117195977718293,"scope":"Independent arithmetic test, not engine or scored replica samples."},"feature_disabled_tuning_seed":60000,"feature_disabled_exact_result_and_diagnostics":true,"retail_only_evaluation_exact_first_three_tuning_rows":true,"repair_exact_256_tuning_rows":true,"no_holdout_seed_reuse":true,"unmodified_run_py_sha256":"54d19a9194ebedee8b947dfaaf8626b1e4ef6f7d1b5aa12e738ec01a5ce401ac"},"solidity_estimate":{"measured":false,"gas_label":"UNMEASURED engineering estimate, not a gas gate result","state":"Reuse the four WAD words already needed for TellPolicy: previous reserveX/reserveY and bid/ask fee. Zero additional persistent words beyond that port; otherwise four uint256 slots (128 bytes). Diagnostic ages/counters are not needed in a contract.","operations":"For each predicted retail callback: invert two reserve-WAD conversions (at most two compatible doubles per reserve in the tested reserve range), reconstruct gamma, 1..4 reserve pairs each with two correctly rounded square roots and a ratio division, expand ratio by +/-2 ulps, deduplicate denominators, and up to three forward divisions/WAD comparisons per denominator. Loose bound in that range: 8 square roots and 60 forward quotient tests; typical denominator count is recorded below.","average_denominator_candidates":3.4939051962124617,"gas_per_predicted_retail_callback_estimate":[60000,220000],"storage_gas_source":"https://raw.githubusercontent.com/ethereum/EIPs/master/EIPS/eip-2929.md","gas_assumptions":"Assumes integer implementations of correctly rounded binary64 helpers, reuse of existing storage, no extra writes for diagnostics. Under EIP-2929, four ordinary clean nonzero-to-different-nonzero slot writes cost about 11600 gas if warm or 20000 if cold, before other operations. Bounds are estimates, not measured upper bounds; no Solidity implementation or afterSwap total was measured."},"commands":["sh fetch.sh \"$B\" replica  # pinned research_base_url; checks both SHA256SUMS manifests","python3 test_quotient.py  # 2 tests; independent 30000-draw synthetic router arithmetic check","python3 verify_no_feature.py  # tuning seed 60000 only; exact baseline ablation","PROCS=8 python3 -I run.py tellpol:TellPolicy 60000 256 tune_base.json soft=1 qm=qm_k1e-5.json","PROCS=8 python3 -I run.py quotient:Policy 60000 256 tune_full.json soft=1 qm=qm_k1e-5.json weight=1  # pre-freeze arithmetic-repair comparison","PROCS=8 python3 -I run.py quotient:Policy 60000 256 tune_repaired.json soft=1 qm=qm_k1e-5.json weight=1","PROCS=3 python3 -I run.py quotient:Policy 60000 3 final_equivalence.json soft=1 qm=qm_k1e-5.json","python3 -I score_once.py  # disjoint checkpoints equivalent to run.py quotient:Policy 10000 2048 holdout.json soft=1 qm=qm_k1e-5.json","python3 -I pair.py holdout.json tell_qm.json","python3 analyze.py  # math.fsum full-precision paired n,mean_diff,se,sum,sumsq,worst5","python3 verify_result.py result.json tell_qm.json  # independently reconstruct paired statistics from bundled score rows"],"provenance":"All score/count/error claims are locally measured by bundled scripts and exact score rows. External algorithm/input provenance is in sources.json; no external board-score prediction is made.","bundle_upstream_runner_note":"Unmodified run.py and pair.py are fetched input sources; pinned SHA256SUMS and freeze manifest identify their exact bytes.","main_source_location":"Complete quotient.py is in code_zb64; reconstruct it beside the bundled scripts."}
