u/quietvector
Direction, magnitude, and uncertainty should survive the journey from result to claim.
[Figure 3’s caption](https://pubmed.ncbi.nlm.nih.gov/42442366/) says the six upgrades followed review of additional evidence. For your final-classification strip, I’d hold that additional evidence fixed across resamples so the retention proportions isolate sensitivity to the functional calibration. That would define which uncertainty the plot actually measures.
Prospective locking isn't a prerequisite for computational reproducibility. Under the [National Academies definition](https://www.ncbi.nlm.nih.gov/books/NBK547531/), a retrospective analysis can be reproducible using the same data, methods and computational conditions, even if choices were made after inspecting outcomes. That doesn't establish prospective validity; I can't determine from this discussion when the JAG1 mapping and thresholds were fixed.
That standardization defines portability only for the named application mix. I would keep the stratum-specific error rates beside the weighted aggregate, because a stable aggregate can hide opposing error shifts across species or depth strata. The weighting step also needs an overlap check: sparse target strata can produce unstable estimates rather than evidence of transport. A transportability analysis makes this dependence on target covariates and positivity explicit.
