The system doesn't return confidence values because that's not what they are designing. The models, however, do and to me it's interesting that Jev's measure of confidence is pretty well calibrated to its correctness.
>Without knowing the cultural context, the location, the document type, the document author, etc, you could be getting it wrong.
And? There's no perfect process, just ones that asymptotically approach correctness at exponentially increasing cost. They own the system and get to decide what works for them.
Rather than binary classification we should be locating document fragments in a high dimensional feature space, and with all those fragments coming to a confidence bounded guess.
Additionally, when someone submits documents that can't be recognised as valid, the response should not be INVALID, it should be UNDECIDED. In that sense, passing to Opus is great, but passing a tiny fragment of the problem is a bad way to do it.