Uncertainties behaving like the LS uncertainties obtained from the GCNN model with 10k logP training samples should be used with caution and the error-based calibration plots reveal the details necessary to do just that. To test whether the problematic uncertainties obtained for the 10k dataset were due to a "bad" selection of training samples, we repeat the analysis for four models trained on different 10k sets of Crippen's logP values. Results are in the supporting information (Tables and and Figures and) but are generally similar to what is presented above.