The accuracy of predictions can be influenced by the basis set, level of theory, and the tautomer used as input. Implicit solvent models are used to represent both octanol and water, and these models are often highly parameterized on experimental solvation free energy data. The abundance of training data contributes to the success of QM methods, much like empirical prediction methods. Solvent models such as SMD , the SM-n series of models , and COSMO-RS are frequently used by SAMPL participants.