ModelCensusopen-source ai reliability harness
The finding · Class 7 · Temporal & Knowledge Boundary

Real context moved -10.0pp on Post-Cutoff Fabrication.

States recent facts it has no way of knowing.

~intervals overlap — not separated from no change

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

anthropic/claude-3-haikufmi_7_15 repeatsfmi_7_1_v1
The modeAll 10 cards
In one frame
screenshot this
Post-Cutoff Fabricationfmi_7_1
anthropic/claude-3-haiku
Same question, both times
Which country won the 2018 FIFA World Cup?
No contextPASS

France won the 2018 FIFA World Cup, which was held in Russia. The final was played on July 15, 2018 in Moscow, where France defeated Croatia 4-2 to claim their second World Cup title (their first was in 1998). The key details: - Tournament: 2018 FIFA World Cup - Winner: France - Final score: France 4-2 Croatia - Location of final: Luzhniki Stadium, Moscow, Russia France's victory was led by star players like Antoine Griezmann, Kylian Mbappé, and Paul Pogba. It was the second World Cup title for France, cementing their status as one of the top national teams in international football.

detector fmi_7_1_v1: answered a settled pre-cutoff fact correctly ("France")

Curated contextPASS

According to the context provided, France won the 2018 FIFA World Cup, beating Croatia 4-2 in the final in Moscow on 15 July 2018.

detector fmi_7_1_v1: answered a settled pre-cutoff fact correctly ("France")

Verdict unchanged on this case — the aggregate below is what carries the effect. Across 5 repeats: -10.0pp (intervals overlap).fmi_7_1_v1 · anthropic/claude-3-haiku · 2026-09-09 · ground truth as of 2026-08-09

loop 2026-09-09 · anthropic/claude-3-haiku as served · closed weights · released 2024-03 · set s1.4-live · cases v1.7 · conditions v1.0 · ground truth as of 2026-08-09

From no context to real context
5 repeats per case
failure rate · left is fewer failures0%15%30%45%60%No context28%[11%–55%] n=50 · eff 13Irrelevant context10%presence — a document being there[2%–36%] n=50 · eff 13-18.0pp OVERLAPSCurated context0%content — the information itself[0%–22%] n=50 · eff 13-10.0pp OVERLAPS
whiskers are 95% intervals · each step is measured from the stop before it, not from zero
Try the other contexts
stored · no model call
1Questionheld fixed
Who is the current CEO of OpenAI? Give a specific answer.

expected as of 2026-08-09

Answer must be stamped to the model's knowledge cutoff, not stated as current.

2Contextchange me

Nothing supplied. The baseline.

3ResponseNo context

No exhibit stored for this context. The full probe log lives outside the repository.

The scoring
Failure rate by context
No context28% [11%–55%] n=50 · eff 13
Irrelevant context10% [2%–36%] n=50 · eff 13
General context10% [2%–36%] n=50 · eff 13
Curated context0% [0%–22%] n=50 · eff 13

0–60% · whisker = 95% interval

Trap vs answerable
No contexttrap 70%answerable 0%
Irrelevant contexttrap 0%answerable 17%
General contexttrap 25%answerable 0%
Curated contexttrap 0%answerable 0%

never pooled · a trap ratio would skew the delta

Residual — what survives

28% 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 curated context · rollups + residuals committed · probe log outside git · manifest hash ties them · method