If we focus on predictions with uncertainty ≤ 2.0 pK a units, our microscopic pK a predictions are comparable to commercially available tools. Of all the microscopic pK a predictions submitted to SAMPL6, only about half the methods included a prediction of uncertainty. Furthermore, ours was the only submission that did not report the same uncertainty value for all predictions. In comparing our results with S+ and ACD we also considered only the points with a predicted uncertainty less than or equal to two pK a units (Figure and). Considering this limited set, there is a significant improvement in overall performance with RMSD's of 1.8 ± 0.2 and 2.1 ± 0.3 compared to S+ and ACD respectively. These smaller RMSD's show that when our method predicts a low uncertainty, it agrees with S+ and ACD as well as those two methods agree with each other. Agreement with established commercial models shows promise for our algorithm and reinforces the importance of expanding our limited training set. Additionally, the ability to predict uncertainty demonstrates the reliability of this approach. While predicting uncertainty is a critical feature for model predictions, our model still needs improvement considering S+ and ACD agree on most microscopic pK a s and both are more accurate than our method for many macroscopic ionization states.