One possible solution to the seeming trade-off between accuracy and computational cost would be the growing use of machine learning (ML) methods in chemistry, particularly as a surrogate for thermochemical parameters.[r] Typically, such methods have been trained to density functional calculations, particularly hybrid B3LYP or B97\(\omega\)