Recognises a metric source unable to produce it
The named source does not hold the data the formula needs.
Can AI do this?
Not settled yet The benchmark tested this, but the models' answers do not settle yet whether they master it. 0 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 55% | Not shown |
| gemini-3.5-flash-lite | Low cost | 52% | Not shown |
| gpt-6-luna | Low cost | 54% | Not shown |
| claude-haiku-5-5 | Low cost | 56% | 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 metric and the source that does
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: GM-011 App onboarding time, source: "Core banking" — onboarding times are in the app and CRM Acceptable: source: "Mobile app onboarding events (CRM)"
Also known as: Source that cannot produce it
Related knobits
Builds on
All 21 knobits of Build the governance scorecard.
Source: Review checklist 06-scorecard, row 11 (DCAM; 25024)