We now assess in Figure Since we have trained strong phase stability classifiers and used a chemically interpretable representation for the surfactants, we can now draw reliable scientific insights from the results presented in Figure , showing feature importances and explanations for the (𝑃 ! , 𝑇 ! ) subsystem. These results for the (𝑃 ! , 𝑇 " ) and (𝑃 $ , 𝑇 ! ) sub-systems are presented in Figure . The results in Figure show that across all three sub-systems the best performing stability classifier was a random forest. This has the beneficial property that we can directly compute feature importances for tree-based models , as shown in Figure (and Figure