The stability score was defined as the relative rank ordering of molecular thermal stabilities, where a molecule with a higher score corresponds to a longer thermal degradation half-life and, consequently, greater stability. In the alkane paper, we demonstrated that this scalar stability metric is easier for models to learn while still offering actionable insights compared to directly predicting half-lives. To enable this, a custom hinge-loss-inspired loss function (Eq. 1) was employed, transforming the regression task into a pairwise classification problem.