The finding · Class 7 · Temporal & Knowledge Boundary

Real context moved -75.0pp on Post-Cutoff Fabrication.

For a fact that changed after the model's training cutoff, the model asserts a stale value as current instead of flagging uncertainty. The rule

openai/gpt-3.5-turbofmi_7_15 repeatsfmi_7_1_v1

The mode All 10 cards

loop 2026-08-15 · openai/gpt-3.5-turbo as served · closed weights · released 2023-03 · set s1.3-live · cases v1.6 · conditions v1.0 · ground truth as of 2026-08-09

From no context to real context

5 repeats per case

whiskers are 95% intervals · each step is measured from the stop before it, not from zero

Try the other contexts

stored · no model call

No exhibits stored for this card.

The scoring

Failure rate by context

No context90% [70%–97%] n=20

Irrelevant context75% [53%–89%] n=20

General context0% [0%–16%] n=20

Curated context50% [30%–70%] n=20

0–100% · whisker = 95% interval

Trap vs answerable

No contexttrap 90%answerable —

Irrelevant contexttrap 75%answerable —

General contexttrap 0%answerable —

Curated contexttrap 50%answerable —

never pooled · a trap ratio would skew the delta

Residual — what survives

90% with no context, 0% under the best supplied source. What survives is 0 failing probes at that best condition. Nothing survives at the best condition on the cases measured here.

Mitigations from the index — the claim

cutoff-aware hedging
retrieval for time-sensitive facts

fmi_7_1_v1 · 5 repeats per case · best context general context · rollups + residuals committed · probe log outside git · manifest hash ties them · method