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COMBO and TwoComp are the cited IdentityMD extensions.","status":"complete_replica_experiment","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  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(gtmcknight)","prune_lost_mass":0.0009999999999998899,"components":4,"moments_preserved":true},"selection_only_choose":true,"report_selected_policy_once_per_seed":true,"gate_exception":"The mandated three-seed baseline Gate P checks precede the report. Neither C nor either flag diagnostic used report seeds before freezing."},"method":{"components":"One current arb point plus each carried prior component conditioned on the no-arb interval. Normalize, prune weights below tau, then merge closest same-current-label pair by moment matching until at most four. No forced Gaussian collapse after two silent steps.","dynamics":"Taylor SIG2=.000945^2; one Gaussian diffusion and no-arb cut per silent step, capped at 12 as in COMBO, then one diffusion for current step.","first_quote":"COMBO weighted branch offsets unchanged; retail branch moments come from all retail components. Carried mixture moments reflect pruning. COMBO hard first classification controls phase and global rival update.","later_fill":"Inverse two-pool constant-product router estimates total retail size for each component using its rival spot; fixed mean 20 and log-sd 1.2 size likelihood times input Jacobian reweights components. Price variance is held within each component; rival is updated to shared marginal price when both pools fill. Only future returned fees change.","pruning":"Discarded probability before renormalization; sequential discarded masses in one observed-step update are combined as 1-product(1-loss). The four-component cap uses merges, not unrecorded deletion.","diagnostics":"First error uses raw pi>.5 on dt>=1, before pruning. Delayed error uses retained current-first arb mass>.5 at last own callback of that timestamp, including pruning. with_later/subset counts restrict to first calls followed by at least one later same-step fill. COMBO has no later update. t=0 is excluded. Each policy is audited on its own closed-loop callbacks on the same seeds.","histogram":"hist bins: loss exactly 0, (0,1e-6], (1e-6,.001], (.001,.01], (.01,.03], (.03,.1], (.1,.3], (.3,1]. Sampled at each observed step end. Silent propagation cuts are attributed to the next observed step update; zero-callback timestamps are not separate histogram entries. Loss fields measure C tau-pruning only; COMBO zeroes do not measure its .005/.995 hard branch collapse.","oracle":"Only intervene(pi,arb) differs: float(true arb) immediately after computed pi, before classification, MIX, posterior, rival, phase, quote. Cflag and ComboFlag are oracle-only, not live policies.","statistics":"Sample variance ddof=1; se=sqrt((sum_d2-sum_d^2/n)/(n-1)/n); wins counts diff>0; worst5 ascending difference.","replica":"replica2.run(seed,policy) defaults: 10000 steps, cfg=None, qcap=None. Standard-library CPython via python3 -I. No engine or contract."},"findings":["Choose selected tau=0.001 by maximum paired mean against COMBO across all 1024 choose seeds.","Report C-COMBO=0.040699448 (SE 0.006635315); C-qt1=0.638090411 (SE 0.013823226), each n=2048.","Report Cflag-ComboFlag=0.000000000 (SE 0.000000000).","The prescribed ComboFlag check matches at six decimals.","choose: first-call error COMBO=16.027605% and C=15.941809%; C delayed=15.944545%. Own closed-loop trajectories, not a common callback trace.","report: first-call error COMBO=16.118613% and C=16.036770%; C delayed=16.038341%. Own closed-loop trajectories, not a common callback trace.","Cflag and ComboFlag have identical report edges on every seed. With the oracle flag, the posterior stays a singleton and this mixture smoother has no remaining branch ambiguity to exploit."],"limitations":["The later-fill likelihood is an approximation: uses a point rival estimate per component and fixed size law; it does not integrate price/rival uncertainty or normalize for callback selection.","Silent propagation remains capped at 12 as in COMBO. No-arb weights below tau are pruned during propagation. Histogram losses for silent cuts are accumulated into the next observed update, not reported separately by physical silent timestamp.","The end-of-step diagnostic uses only fills already observed, including current-step pruning; no earlier fee is revised. First-call vs delayed differences on the subset with later fills isolate that timing population, but may include pruning.","The offline bundle reproduces policies and screens without dependencies. The original 12-value gates.py check additionally requires the pinned upstream tables; its observed stdout and hashes are recorded here.","Per-component rival estimates are retained within a step, then initialized from the shared COMBO rival estimate at the next first callback; only the price mixture is carried across steps.","No contract, Gate F, gas, engine, or leaderboard result is claimed."],"source_bundle":{"format":"base64(zlib(UTF-8 JSON 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"},"regeneration_commands":["python3 -I -c \"import json,zlib,base64,pathlib,sys; d=json.load(open(sys.argv[1])); files=json.loads(zlib.decompress(base64.b64decode(d['source_bundle']['data']))); root=pathlib.Path(sys.argv[2]); [( (root/p).parent.mkdir(parents=True,exist_ok=True), (root/p).write_text(t)) for p,t in files.items()]\" result.json scratch/repro","python3 -I scratch/repro/w/regenerate.py","python3 -I scratch/repro/w/gate_check.py","python3 -I scratch/repro/w/check.py","python3 -I scratch/repro/w/unit_check.py","python3 -I scratch/repro/w/screen.py choose 64000 65024 8 combo qt1 c:0.001 c:0.01 c:0.03 c:0.1","python3 -I scratch/repro/w/screen.py choose_flags 64000 65024 8 comboflag cflag:0.001","python3 -I scratch/repro/w/screen.py report 10000 12048 8 combo qt1 c:0.001 comboflag cflag:0.001","python3 -I scratch/repro/w/report_stats.py"],"regeneration_notes":"Repeat each checkpointed screen command until full coverage; each exits after at most ~420s plus startup/cleanup. Frozen tau is supplied; do not reselect from report. All generated state remains below scratch/repro. Use summarize.pair/audit on regenerated checkpoints for statistics.","provenance":{"measurements":"Local screen.py checkpoints summarized by summarize.py; hashes and runnable source bundled. Not independently certified.","harness_repair":"An initial choose probe stopped on an overly strict raw-fee <=10% assertion. It was corrected to validate finite raw fees and capped stored fees, matching replica2 clampf. Its 15 completed rows were retained; policy code did not change."}}