Recognises a transformation on a column the source lacks
A transformation reads a field the source does not have.
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 | 76% | Not shown |
| gemini-3.5-flash-lite | Low cost | 43% | Not shown |
| gpt-6-luna | Low cost | 76% | Not shown |
| claude-haiku-5-5 | Low cost | 74% | 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 field name from the profile
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: MP-014 card_txn.mcc <- SR-002.merchant_category; the settlement file has mcc_code Acceptable: The field name from the source profile
Also known as: Transformation on a column the source lacks
Related knobits
Builds on
All 18 knobits of Map sources to targets.
Source: Review checklist 02-source-to-target-mapping, row 12 (DMBOK)