Explains the population, measure and threshold of a check
The rows a check examines, what it counts, and the pass rate it requires.
Can AI do this?
AI does this well Most of the tested AI models master this. 9 of 10 models master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 100% | Mastered |
| gemini-3.1-pro-preview | Flagship | 100% | Mastered |
| gpt-6-astra | Flagship | 100% | Mastered |
| claude-fable-5-1 | Flagship | 100% | Mastered |
| gemini-3.8-flash | Mid tier | 100% | Mastered |
| gpt-6.1-sol | Mid tier | 100% | Mastered |
| claude-sonnet-5-5 | Mid tier | 100% | Mastered |
| gemini-3.5-flash-lite | Low cost | 98% | Not shown |
| gpt-6-luna | Low cost | 100% | Mastered |
| claude-haiku-5-5 | Low cost | 100% | Mastered |
Mastered means a probability of at least 90% that the model has this knobit, estimated from its graded answers. “Not shown” means the answers do not settle it either way. How the models are tested.
What it looks like in practice
Expected result: The rows a check examines, what it counts, and the pass rate it requires
How it is assessed: States the population and threshold sample rules imply
Related knobits
Needed for
- K-703 Recognises a constraint deferred without a check
- K-713 Recognises a check measuring the wrong population
- K-720 Recognises a threshold at odds with its rule
- K-726 Recognises an empty population reported as a pass
- K-755 Explains severity, threshold and failure action
- K-757 Explains segmented data quality reporting
All 31 knobits of Derive data quality rules.
Source: Data-management practice used by the stage 7 reference and review checklist