Comparing the alkane stability score and BDFE models reveals that the increased chemical coverage of BDFE training provides limited advantages in the polymer prediction task (Figs. and). The overall performance between the models is comparable, with the higher accuracy of the alkane stability score on CH polymers demonstrating that the increased data quality for this subset is the distinguishing factor for improved performance. Additionally, since alkane degradation is primarily radical-based, the alkane model performs similarly to minimum BDFE on chain-growth polymers. The higher performance of both models on chain-growth polymers is also supported by the fact that a significant factor in polymer pyrolysis is depolymerization, which for chain-growth polymers proceeds through a radical elimination mechanism similar to alkane pyrolysis or a first-order homolytic cleavage approximation. The lack of depolymerization information for condensation/step-growth polymers in both these models results in poorer performance. For these tests, trimers were used as small molecule surrogates, as they are the smallest oligomer unit capable of capturing neighboring effects. Dimers and tetramers were also tested, and while minor gains were observed when moving from dimers to trimers, no significant improvement was observed when moving from trimers to tetramers (Fig. and Fig. ).