Hi Victor,
That’s an interesting suggestion. I’m not sure how happy I would be to abandon C. albipunctata suggestions, since the model knows it quite well.
I like to say that the model is almost entirely the product of the iNaturalist identification community - and within Psychodidae, the iNat community has only been interested in C. albipunctata since before we started doing computer vision, to the exclusion of the other ~2,600 described species in the family.
If you have any links to papers on the subject of computer vision for hierarchical taxonomies, I’d be delighted to look them over. Our investigations of training with both positive and negative identifiers were not promising, and they are complicated by the difficulty of teasing out identifier intent for non-species identifications. The best approach we were able to devise looked good for accuracy but was prohibitively expensive.
By this I mean:
label x: is Psychodidae but not Clogmia
label y: is Psychodidae, is Clogmia but not C. albipunctata
label z: is Psychodidae, is Clogmia, is C. albipunctata