Task gallery / Machine learning / Version 1
Reference solution (oracle)
Pass
No-op resistance check
Pass
QA verdict
Not recorded
Aggregate eligibility
Eligible version

The task

Two health surveys measure the same condition in different ways. One is a large telephone survey where adults report a prior diabetes diagnosis (a self report); the other is a smaller in-person survey where diabetes comes from a lab measurement. All files sit in [local evidence] Train on the telephone respondents (brfsstrain.csv) and predict, for every person in the in-person scoring cohort (nhanestest.csv), the calibra…

Excerpt only; not a complete executable task specification. Task ID task_f13252be591241dd · version 1. Selection status: not fully recorded.

Results by model and effort

This exact task version only. Every rate is passes / valid runs with a Wilson 95% interval; n≤2 remains counts only. Macro aggregation does not apply within a single task. Baselines are summarized in the quality gates, not ranked. A passed no-op resistance check means that doing nothing did not solve the task.

Current evidence

Model / effortVerifier result [95% Wilson]Diagnostic labels / validHARNESS_ERROR · excludedOutcome classes
Claude Opus 5 · default (unverified)5/5 · 100.0% [56.6%, 100.0%]5 / 50
GOOD_FAILURE: 0
BAD_FAILURE: 0
GOOD_SUCCESS: 5
BAD_SUCCESS: 0

Legacy evidence

Model / effortVerifier result [95% Wilson]Diagnostic labels / validHARNESS_ERROR · excludedOutcome classes

Difficulty, with uncertainty

Selected-best difficulty: 0.0% [0.0%, 43.4%]. This is one minus the best measured current-row pass rate among rows with at least five valid runs.

The maximum is selected from the observed rows, so the estimate is optimistic. Its Wilson interval is not adjusted for model selection. “Hard” requires qualifying GOOD_FAILURE evidence; the threshold flag additionally requires the interval and recorded quality gates to meet the documented rule. This is not independent validation. Threshold flag: no.

Every recorded run

7 recorded trials, including controls. Diagnostic labels do not replace verifier reward. Labels and quality checks are source declarations, not independently attested here. Internal evidence remains private; a missing public URL is shown explicitly. Records with invalid or absent rewards are not scored.

Run / modelDate / sourceReward / eligibilityDiagnostic class / sourceResourcesEvidence
trial_7ed9b264c361407e
oracle@@
Oct 11, 2026
console
1 · validNo diagnostic label
derived
Tokens: —
Turns: —
Cost: —
Not publicly available
trial_828f73c209884bea
nop@@
Oct 11, 2026
console
0 · validNo diagnostic label
derived
Tokens: —
Turns: —
Cost: —
Not publicly available
trial_6125c09b9cc64ea8
Claude Opus 5 · default (unverified)
Oct 11, 2026
console
1 · validGOOD_SUCCESS
frozen-classifier
Tokens: 46,548
Turns: 38
Cost: $2.9040
Not publicly available
trial_8407205977644799
Claude Opus 5 · default (unverified)
Oct 11, 2026
console
1 · validGOOD_SUCCESS
frozen-classifier
Tokens: 75,776
Turns: 28
Cost: $3.6792
Not publicly available
trial_8ed97665e784407e
Claude Opus 5 · default (unverified)
Oct 11, 2026
console
1 · validGOOD_SUCCESS
frozen-classifier
Tokens: 35,723
Turns: 16
Cost: $1.7430
Not publicly available
trial_9e248c22c67342dc
Claude Opus 5 · default (unverified)
Oct 11, 2026
console
1 · validGOOD_SUCCESS
frozen-classifier
Tokens: 42,944
Turns: 21
Cost: $2.1254
Not publicly available
trial_bf647531422e4759
Claude Opus 5 · default (unverified)
Oct 11, 2026
console
1 · validGOOD_SUCCESS
frozen-classifier
Tokens: —
Turns: —
Cost: —
Not publicly available