We conducted a comprehensive analysis of the ID performance, OOD performance, and the performance gap (difference between ID and OOD ROC-AUC values) across all the splitters, data sets, and models. Our primary objective was to investigate whether classical ML and GNN models behave differently on OOD data or if they follow a similar pattern.