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

A clinical team ran a two arm trial and needs a dependable read on how often patients relapse in each arm and how much the treatment shifts it. The pipeline at /app/analysis.R runs end to end, but its relapse numbers come out too high and climb the longer you look. Rebuild it into numbers a regulator would accept. The extract is a raw export, not a clean cohort: inconsistent outcome coding, missing baseline fields, …

Excerpt only; not a complete executable task specification. Task ID task_f7586e597c254079 · 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_9f3b6beddbb747e1
oracle@@
Oct 11, 2026
console
1 · validNo diagnostic label
derived
Tokens: —
Turns: —
Cost: —
Not publicly available
trial_c2c2d40696ea49bb
nop@@
Oct 11, 2026
console
0 · validNo diagnostic label
derived
Tokens: —
Turns: —
Cost: —
Not publicly available
trial_1b812c86cf494df3
Claude Opus 5 · default (unverified)
Oct 11, 2026
console
1 · validGOOD_SUCCESS
frozen-classifier
Tokens: 37,764
Turns: 29
Cost: $2.2072
Not publicly available
trial_54c4ea3ab21e47e2
Claude Opus 5 · default (unverified)
Oct 11, 2026
console
1 · validGOOD_SUCCESS
frozen-classifier
Tokens: 31,097
Turns: 29
Cost: $2.0526
Not publicly available
trial_64994ff2c3b345ac
Claude Opus 5 · default (unverified)
Oct 11, 2026
console
1 · validGOOD_SUCCESS
frozen-classifier
Tokens: 40,715
Turns: 26
Cost: $2.2667
Not publicly available
trial_8803c086c9fe468a
Claude Opus 5 · default (unverified)
Oct 11, 2026
console
1 · validGOOD_SUCCESS
frozen-classifier
Tokens: 47,292
Turns: 33
Cost: $2.8318
Not publicly available
trial_fee3917cdd7e43ea
Claude Opus 5 · default (unverified)
Oct 11, 2026
console
1 · validGOOD_SUCCESS
frozen-classifier
Tokens: 39,596
Turns: 24
Cost: $2.1395
Not publicly available