We can assess the accuracy difference between the "train" and "test" sets by evaluating the performance of pKa-ANI on a lysine pK a subset that has been used to train the predictor. While in terms of AUE the performance of the ML based predictor becomes only insignificantly worse, the reduction in the Pearson correlation coefficient between the "test" subset and the "training" set is significant. Given the small size of the "test" dataset and bias toward only one residue type, this evaluation of pKa-ANI accuracy should not be overinterpreted. Nevertheless, our analysis suggests a reduction in prediction accuracy when using independent test data, a result consistent with the original pKa-ANI publication .