Evidence and limits
Finding: Optimizing a model for the combined human-machine result can outperform optimizing the model alone when human error patterns are known.
Impact: Watch complementary-error allocation as a candidate evaluation. Reject stand-alone model accuracy as the only routing signal.
Boundary: The tasks are structured and depend on labeled or estimable human behavior. Next: how can complementary error regions be estimated without profiling people beyond the owning workflow's need?
Flags: known-label tasks; modeled human behavior
Record State: Catalog review recorded; not a performance endorsement
What was reviewed: Structure and relevance screened; not a full evaluation