stating a transfer-learning problem

I am trying to re-state the problem of putting labels on SDSS-IV APOGEE spectra as a transfer learning problem, since the labels come from (slightly wrong) stellar models. Or maybe domain adaptation. But the form of the problem we face in astronomy is different from that faced in most domain-adaptation contexts. The reasons are: The simulated stars are on a grid, not (usually) drawn from a realistically correct distribution. There are only labels on the simulated data, not on the real data (labels only get to real data through simulated data). And there are selection effects and noise sources that are unique to astronomy.