To gain more insight into the impact of the modified training sets on predictive performance, we computed the average predicted SOM-probabilities for halogen atoms and analyzed the distribution of halogens classified as positive or negative. The results revealed clear patterns: the baseline model correctly classified all halogen atoms as negatives. In contrast, the halogen-agnostic model produced nearly random predictions, with an average SOM-probability of 0.4 ± 0.2. In the noisy halogens model, where 20% of labels were intentionally mislabeled as positive, the average predicted SOM-probability was 0.4 ± 0.1, with a positive-to-negative ratio of 55 : 172 (24%).