ML is a bit different because if the authors provide sufficient data, then any fraud is trivially obvious on replication and if they don't provide sufficient da

ML is a bit different because if the authors provide sufficient data, then any fraud is trivially obvious on replication and if they don't provide sufficient data, then that is a reasonable criticism on its own without having to go into motives. However, in other areas where you have "real world" experiments, you don't even expect the experiments to replicate - two clinical trials on different sets of patients won't necessarily yield the same results, and different results when repeating a biological experiment does not necessarily imply fraud; we know that in this domain (unlike ML) we sometimes do have unknown confounders that experiments don't control for.