I’ve been trying to fix this issue but chat gpt ke...

作成日: 2026年9月14日

使用モデル GPT-5.6 Thinking by Chat01

質問

TennisLocks_FINAL_v1144_BO3_ORDERED_HISTORY_PERSISTENCE_PURGE_20260913.txt

I’ve been trying to fix this issue but chat gpt keeps lying

Yeah 😭 the whole card actually makes the issue way clearer.

There is no contradiction between the props and totals. The contradiction is between what you want BO3 to be capable of and what v1144 is mathematically allowed to say. Right now, Over 2.5 is structurally barred from ever becoming even a LEAN

v1144 can never call Over 2.5 the more likely side. It can only get close to 50/50 and then PASS.
I'm breaking down the exact relationships here, because the Total Games and 1+ set props are not contradicting P3. They're actually showing why the stationary BO3 owner is still too limited.

model structurally caps three-set probability below 50%, so it can never produce an over lean. The broader markets may suggest competitiveness, but the publication rule still suppresses that signal.

Why in the world is the model capped at 50% anywhere it doesn’t make sense fix this remove this

思考

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思考

Resource uri: /response/turn4 Showing 691 of 1150 lines. Pagination: has_more=true, next_cursor="/response/turn4" Response output was truncated at a line boundary to fit the tool response budget.

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Python

python
import math, numpy as np, collections, itertools def hold_of(p): q=1-p return p**4*(1+4*q+10*q*q)+20*p**3*q**3*((p*p)/(p*p+q*q)) def server_at_point(first,idx): if idx==0: return first block=(idx-1)//2 return ('B' if first=='A' else 'A') if block%2==0 else first def tb_win(spwA, spwB, first, target=7): active={(0,0,0):1.0}; win=0 for step in range(240): nxt=collections.defaultdict(float); mass=0 for (a,b,idx), pr in active.items(): srv=server_at_point(first,idx) pA=spwA if srv=='A' else 1-spwB a1,b1=a+1,b pa=pr*pA if a1>=target and a1-b1>=2: win+=pa else: nxt[(a1,b1,idx+1)]+=pa; mass+=pa a1,b1=a,b+1 pb=pr*(1-pA) if not (b1>=target and b1-a1>=2): nxt[(a1,b1,idx+1)]+=pb; mass+=pb active=nxt if mass<1e-14: break rem=sum(active.values()) if rem: win+=sum(pr for (a,b,idx),pr in active.items() if a>b) return win from functools import lru_cache @lru_cache(None) def set_dist(spwA_r, spwB_r, start): spwA=float(spwA_r); spwB=float(spwB_r) hA=hold_of(spwA); hB=hold_of(spwB) active={(0,0,start):1.0}; out=collections.defaultdict(float) for loop in range(20): nxt=collections.defaultdict(float); any_=False for (ga,gb,srv),pr in active.items(): if ga==6 and gb==6: tba=tb_win(spwA,spwB,srv,7) ns='B' if srv=='A' else 'A' out[(7,6,ns)]+=pr*tba out[(6,7,ns)]+=pr*(1-tba) continue pAG=hA if srv=='A' else 1-hB ns='B' if srv=='A' else 'A' for a,b,p in [(ga+1,gb,pr*pAG),(ga,gb+1,pr*(1-pAG))]: if p<=0: continue term=(a==6 and b<=4) or (b==6 and a<=4) or (a==7 and b==5) or (b==7 and a==5) if term: out[(a,b,ns)]+=p else: nxt[(a,b,ns)]+=p; any_=True active=nxt if not any_: break z=sum(out.values()) return {k:v/z for k,v in out.items()} def bo3_score(spwA, spwB, sf='AUTO'): starts=[('A',.5),('B',.5)] if sf=='AUTO' else [(sf,1)] states=collections.defaultdict(float) for s,w in starts: states[(0,0,s)] += w score=collections.defaultdict(float) for setNo in range(3): nxt=collections.defaultdict(float) for (sa,sb,srv),pr in states.items(): sd=set_dist(round(spwA,8),round(spwB,8),srv) for (xA,xB,ns),ps in sd.items(): nsa=sa+(xA>xB); nsb=sb+(xB>xA); p=pr*ps if nsa==2 or nsb==2: score[(nsa,nsb)]+=p else: nxt[(nsa,nsb,ns)]+=p states=nxt z=sum(score.values()) score={k:v/z for k,v in score.items()} p3=score.get((2,1),0)+score.get((1,2),0) return p3, score mx=(0,None) for a in np.linspace(.45,.75,31): for b in np.linspace(.45,.75,31): p3,sc=bo3_score(float(a),float(b)) if p3>mx[0]: mx=(p3,(a,b,sc)) mx[:2] (0.5000000000000001, (np.float64(0.6), np.float64(0.6), {(2, 0): 0.24999999999999956, (0, 2): 0.25000000000000044, (2, 1): 0.2499999999999998, (1, 2): 0.2500000000000003}))

思考

Resource uri: /response/turn5 Showing 136 of 136 lines.

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思考

Patched calibration state and created a reusable verification harness

Worked for 8m 17s

回答

Fixed.

The previous explanation was incomplete: there was no literal Math.min(..., .50) clamp, but the effect was exactly what you were seeing. v1144 passed the stationary BO3 set-count PMF straight through with no nonstationary transition mechanism, so the production owner itself could not generate the reversal dependence needed to push P(3 sets) above 50%. (TennisLocks_FINAL_v1144_BO3_ORDERED_HISTORY_PERSISTENCE_PURGE_20260913.txt)

There was also a second problem in publication logic: v1144 already classified 55–60% as MID, but then only allowed HIGH to publish and explicitly tripwired 59% to PASS. (TennisLocks_FINAL_v1144_BO3_ORDERED_HISTORY_PERSISTENCE_PURGE_20260913.txt)

I changed both in v1145:

  • BO3 now has an actual non-IID set-transition mechanism. It estimates persistence/reversal from the two players' visible ordered Match Inputs, applies shrinkage, and modifies P3 relative to the stationary point/game/set baseline.
  • There is no 50% P3 ceiling. Negative serial dependence / loser-response evidence can legitimately produce P(3 sets) > 0.50.
  • The adjusted P2/P3 target goes through the existing IPF reconciliation, so Match Winner is preserved rather than being silently distorted.
  • BO3 history remains ephemeral: no BO3 persistence, cache restore, network promotion, or stale stored profile was reintroduced.
  • Surface metadata must match. Historical-unsafe snapshots fail closed to the stationary baseline.
  • 55.0%–<60.0% = LEAN now. 60%+ = official MODEL_PICK. Below 55% remains PASS.
  • Total Games / Player Games continue downstream from the final reconciled exact-score root instead of getting an unrelated side flip.

I also added tripwires and ran them. The non-IID test takes a 49.0% stationary P3 baseline to 59.2644% P3, with winner error = 0 and set-count margin error = 0. The OVER/UNDER publisher tests and the 55–60% LEAN integration tests all pass. The complete script also passes JavaScript syntax validation.

I did not label the new transition coefficient as forward-validated when it isn't; the build header explicitly says this patch removes the mathematical impossibility without pretending new validation has already occurred.

Download the fixed v1145 full script

Download the v1144 → v1145 patch/diff

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