Its additive model suggested that the original ratio of actives in test explained the predicted proportions, rather than the training ratio. We also found that the number of interactions per protein was a relevant factor: the more interactions, the less active proportion, suggesting that the extreme cases with all predicted as actives tended to be proteins with few interactions.