Conformal prediction is indeed an interesting method (or family thereof). I can’t comment on our undisclosed internal machine learning research, but what I can say is that machine learning on biological problems tends to be much, much harder than that on common toy or benchmarking datasets. Uncertainty quantification is usually an even harder problem than pure accuracy measurement, especially when you have a mix of known and unknown systematic and random effects in your data-generating process.