A second problem is that f conf ignores the output of the model.
if candidate A has a confidence interval around [0.6, 1] and candidate B has a confidence interval around [0.4, 0.7], then f conf will prefer candidate A, even though training on A will not change the hypothesis's performance, since the entire confidence interval is already in the noun zone.