Recognises a data quality issue closed with no verification
Closed with no re-measurement recorded.
Can AI do this?
People still lead Few or none of the tested AI models showed they master this. 0 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 89% | Not shown |
| gemini-3.5-flash-lite | Low cost | 9% | Not shown |
| gpt-6-luna | Low cost | 9% | Not shown |
| claude-haiku-5-5 | Low cost | 9% | Not shown |
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 re-run measurement over the affected population and its result
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: IS-004 GL break closed, verification.result: null, "snapshot re-run" Acceptable: Re-run of QM-005 for 30 Sep and 31 Oct: 0 breaks
Also known as: Closure with no verification
Related knobits
Builds on
All 9 knobits of Manage data quality issues.
Source: Review checklist 06-issue-management, row 3 (8000-61; ITIL)