Recognises a lossy amount conversion
Amounts cast to a precision that loses minor units, or the currency dropped.
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 | 83% | Not shown |
| gemini-3.5-flash-lite | Low cost | 50% | Not shown |
| gpt-6-luna | Low cost | 83% | Not shown |
| claude-haiku-5-5 | Low cost | 79% | 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 mapping and the conversion by currency
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: MP-002 CAST(amount AS DECIMAL(15,2)) for all currencies; BHD has 3 decimals Acceptable: Amount in minor units with its currency, or a scale per currency
Also known as: Lossy amount conversion
Related knobits
Builds on
Usually followed by
All 18 knobits of Map sources to targets.
Source: Review checklist 02-source-to-target-mapping, row 2 (4217; DMBOK)