We categorized the data points into three groups: (1) those with an MCC of 0 (blue diamonds), (2) outliers (orange squares), and (3) the remaining data points (green dots). These differences arise from the varying difficulty in predicting positives and negatives. Many negative atoms, like quaternary carbons, are easily predicted as non-SOM, resulting in low-uncertainty bins with very few or no predicted positives. For example, the first seven bins have fewer than 10 true positives and no predicted positives, giving an MCC of 0. In the second category, a strong class imbalance makes the metric unstable, with only 2 predicted positives out of 413 negatives. However, in the third category, the positive-to-negative ratio improves (2.6% -48%), leading to more reliable MCC values. Excluding bins with unreliable metrics, we find a strong negative correlation (ρ = -0.97) between total uncertainty and MCC, indicating the model's confidence aligns well with its predictive performance.