Explains the non-functional data concerns
Volume and growth, retention and end of life, classification and access, source and ownership.
Can AI do this?
People still lead Few or none of the tested AI models showed they master this. 1 of 10 models master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 99% | Mastered |
| gemini-3.1-pro-preview | Flagship | 87% | Not shown |
| gpt-6-astra | Flagship | 96% | Not shown |
| claude-fable-5-1 | Flagship | 98% | Not shown |
| gemini-3.8-flash | Mid tier | 91% | Not shown |
| gpt-6.1-sol | Mid tier | 97% | Not shown |
| claude-sonnet-5-5 | Mid tier | 97% | Not shown |
| gemini-3.5-flash-lite | Low cost | 89% | Not shown |
| gpt-6-luna | Low cost | 88% | Not shown |
| claude-haiku-5-5 | Low cost | 89% | 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: Volume and growth, retention and end of life, classification and access, source and ownership
How it is assessed: Names the concerns a sample register leaves uncovered
Related knobits
Needed for
- K-128 Recognises an uncovered volume or retention requirement
- K-129 Recognises an uncovered sensitivity or access requirement
- K-130 Recognises an uncovered lineage requirement
All 47 knobits of Capture data requirements.
Source: Data-management practice used by the stage 1 reference and review checklist