The performance of the two formalisms was tested by performing a linear regression of logDEq.1 and logDEq.2 on their experimental values. The root-mean-squared error (RMSE), mean absolute error (MAE), mean squared error (MSE), and Pearson's correlation coefficient squared (R 2 ) were calculated with the 'Metrics' package in R. We also tested the performance of each formalism on each individual molecule using the descriptor d3 (Eq. 5). When d3 yielded a value greater than zero, Eq. 2 fits better than Eq. 1. Accordingly, we created a binomial conditional based on the values of d3, where Eq. 2 should be used when d3 is greater than 0.2 (see Results and Discussion); otherwise, both equations are considered equivalent, which can be interpreted as Eq.