Recognises a data fix applied at the symptom
The rows corrected, the process that produced them unchanged.
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 | 83% | Not shown |
| gemini-3.5-flash-lite | Low cost | 81% | Not shown |
| gpt-6-luna | Low cost | 83% | Not shown |
| claude-haiku-5-5 | Low cost | 83% | 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 cause in the process and the fix at its level
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: CA-001 recalculates days_past_due for 1,100 migrated loans; MP-311 unchanged Acceptable: Cause: MP-311 writes 0 where the source has no value; correct MP-311 logic, recompute from the schedule
Also known as: Fix applied at the symptom
Related knobits
Builds on
All 9 knobits of Analyse the root causes.
Source: Review checklist 05-root-cause-analysis, row 1 (9001 10.2.1(b); DMBOK)