For the complete dataset and the drug-like subset, the critical SHAP leverage values (h * ) were 3.86 and 3.58, respectively. In the complete dataset, 1539 data points corresponding to 163 compounds exceeded the h * threshold, while in the drug-like subset, 969 data points corresponding to 101 compounds were beyond this limit, indicating that predictions for these compounds may be less reliable. In the complete dataset, these 163 compounds included a significant number of salts, dyes, and metal-containing compounds, which often exhibit unique structural features (e.g., specific cations or anions, large number of functional groups) that complicate predictions. These features may not be sufficiently represented in the training set, leading to anomalous SHAP values and leverage. However, it is worth noting that the prediction errors (standardized residuals) for these structurally distinct compounds were not excessively large. This may be attributed to the fact that compounds with high leverage values can represent unusual yet valid samples that the model interprets correctly, suggesting that the model is well-trained on the primary dataset and demonstrates robustness and strong generalization capabilities.