The POM approach employed the message-passing neural network classifier. The molecules were encoded into adjacency and feature matrices. The feature matrix includes binary features regarding each atom's atomic type, bonding properties (orbitals hybridization), and the presence of a chirality center. The target variable was a 138-dimensional binary vector, indicating an odorant's membership in various olfactory families.