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truncated belief and updates retail count/rival sync on an actual arb. Both alter future quotes and paths; counts alone cannot identify the causal cost of either error type."},{"bucket_localization":"size:small","share_of_first_callbacks":0.46676689082604583,"share_of_errors":0.6470478288307481,"error_rate":0.239919726,"predicted_arb_rate":0.524596201,"actual_arb_rate":0.56286274,"oracle_gain_fraction_of_full":0.6847668468383445,"interpretation":"Descriptive marginal localization; oracle gain fractions overlap and are not additive. Bucket selection was fixed from choose.","source":"Baseline report counts/calibration and separately paired report-policy measurements."},{"bucket_localization":"phase:1","share_of_first_callbacks":0.46150178319928176,"share_of_errors":0.48748588127002246,"error_rate":0.182817714,"predicted_arb_rate":0.493513284,"actual_arb_rate":0.50912655,"oracle_gain_fraction_of_full":0.7159055836571178,"interpretation":"Descriptive marginal localization; oracle gain fractions overlap and are not additive. 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","bundle_sha256":"cffbc2f06cad8ecfe16aa40952d70fc25f23fc72f0d7ec890fde525a3f1d351c","extract":"import json,zlib,base64,pathlib; r=json.load(open(RESULT)); files=json.loads(zlib.decompress(base64.b64decode(r[\"reproduction\"][\"bundle_zlib_base64\"]))); [(pathlib.Path(k).parent.mkdir(parents=True,exist_ok=True),pathlib.Path(k).write_bytes(v[\"data\"].encode() if v[\"encoding\"]==\"utf8\" else base64.b64decode(v[\"data\"]))) for k,v in files.items()]","commands":["Offline scoring: python3 -I test/scratch/scratch/verify.py","Optional input/gates regeneration with network: python3 -I test/scratch/scratch/regenerate.py; cd test/scratch/amm-sim/research/solved && python3 -I gates.py","For i=0..3: python3 -I test/scratch/scratch/driver.py choose (64000+256*i) 256 test/scratch/scratch/choose{i}.jsonl > test/scratch/scratch/choose{i}.meta.json","python3 -I test/scratch/scratch/summarize.py freeze","For i=0..3: python3 -I test/scratch/scratch/driver.py ablate (64000+256*i) 256 test/scratch/scratch/ablate{i}.jsonl > test/scratch/scratch/ablate{i}.meta.json","For i=0..7: python3 -I test/scratch/scratch/driver.py report (10000+256*i) 256 test/scratch/scratch/report{i}.jsonl > test/scratch/scratch/report{i}.meta.json"],"data_checksums_sha256":{"choose0.jsonl":"9bed176afcfd144954b80902bb59c377b2ef4fa2bcd58951e7a909d0ae6b777b","choose1.jsonl":"f68226b5f564d8cc749fc684867c04f9c51d76cb8e2d6aab20d3e54dee3563fb","choose2.jsonl":"2de26409d89034718a263801173d05913746e00cd6a61814423fe2b843fd1aa1","choose3.jsonl":"6803388ae635a6e4bc39edd799d993044aa6ad21b74232f89aa57fd8ed2b8e32","ablate0.jsonl":"e33fd2764c7d3d7d3a7713f9b5028ed8d52bd930b014750c4e841df5bc9ed83e","ablate1.jsonl":"c3b46b0b5860257594f8db9b0b8e1598a8adfbc0902f6e3b5559c87560cdb3f2","ablate2.jsonl":"d2e88a223b8137b5ad7f196fd57526851d938ad01d4d82818f535eb989b408ef","ablate3.jsonl":"7ac90f6412ac57393183d811aaf77ccd334bcf04995a931a6c544d13f9100dcd","report0.jsonl":"f940e51729b41d774f21ae0160d4b7fb51a4e336ca9ff1cff947c8e2fa7eb6f9","report1.jsonl":"f08256ea5fb0830b33aca6164269cabff6ae7739b507b3b321fc874655ee89b7","report2.jsonl":"c23d41678c4d1ecf7505e8e470763cebcf8eb804e45d115b3503e97c1ac28196","report3.jsonl":"39e3a751647882d808b2ba027dd0ad32c947b9eeee2addef22f86af0183280b0","report4.jsonl":"cff1677af5f14c9dd48e21afbd41dfcd548e6b73d5eb23addeb3f1db90e49f48","report5.jsonl":"ac96fd9003ac4af82e592543af31847fb236aeab6acf68b81f585baf83e4845b","report6.jsonl":"c2ef9b42491c9329faa071d3070aa711d796925d45e767da28a1a3bbdee478a8","report7.jsonl":"9c994a30164650d82752aa2d7fb4b18b6cdd58c9bc25740235b85430deb07f67"},"se_formula":"sqrt((sum_d2 - sum_d^2/n)/(n-1))/sqrt(n)","note":"Do not regenerate frozen_unix to reproduce its hash; the included frozen.json is the actual pre-report artifact. Raw JSONL regeneration is deterministic; metadata timings are not."},"proposed_observable_features":["Trade amountY and normalized log spot movement relative to fees and predicted volatility, conditioned on previous inferred phase.","Time since inferred pin and time since own callback; retain a soft pin-confidence/history feature rather than a hard age alone.","Previous direction/size sequence and inferred rival-sync status; test calibration jointly with phase and size on fresh choose seeds before any report evaluation."]}