Actually, it seems more random from training run to training run than related to the composition of training data I think, I don’t see a consistent pattern. But different models, run on the same micrographs, seem to “flatten” different sets of particles.
It makes me wonder if to get the most good picks, it may be worth taking a consensus approach (picking on mics denoised with independently trained models & taking the union)
