This use case demonstrated how CIME can be used to effectively compare attributions from two models (T3) through the exploration of a chemical space (T1), and might increase user trust in predictions made by an interpretable model. Additionally, based on the highlights, a medicinal chemist could identify ways of modifying the compounds to decrease their lipophilicity. A similar workflow could be used for comparing two (or more) attribution methods for a single model.