Already happening unfortunately

> Confirms

> we can infer

Hmmm

This is honestly a better idea than any intuition I can give you.

Also anecdotally, I have encountered situations where one batch of replicates was either much lower quality or somehow different than the rest and we ended up dropping those by first finding them using an empirical setup similar to the one described above.

I would recommend using all of the replicates. The model should learn the expectation sans any mean-zero noise that might vary between them. Basing this on a hand wavy interpretation of some results from the original noise2noise paper and more recent work on SSL. You can even consider each replicate an "augmentation" of your ground truth mean and use principles of SSL to enforce consistency between the replicates.