You can also feed the document or source file to another frontier-level model, ideally two others, and tell it to vet it aggressively. The goal is to goad the models into erring on the side of false positive findings rather than potentially missing true positives.

I find that if Gemini Pro agrees with Claude Opus 4.8 and GPT 5.5 on something, it's almost certainly correct at a level where I wouldn't be likely to catch any errors myself.