Question 160
CCA-F is a newly released exam. These practice questions reflect our best current understanding — the exact wording and question formats may change in the live exam until the certification matures. Use them to learn the concepts, not to memorize.
Scenario: Structured Data Extraction - A document-extraction pipeline reports 96% overall accuracy and the team wants to fully automate it. A spot check reveals that one document type — handwritten intake forms — has roughly 38% errors, hidden inside the aggregate metric. What practice would have surfaced this risk earlier?
- ATrust the 96% aggregate and automate everything.
- BIncrease `max_tokens` for all extractions to reduce errors.
- CAnalyze accuracy by document type and field, using stratified random sampling rather than relying on the aggregate.
- DAsk the model to self-rate its confidence on each document and trust it.