Therefore, the accuracy of predictions for these polymers remains hindered by the scarcity of high-𝑇 ! polymer data in the training set. To address this issue, future efforts should be directed toward augmenting the training dataset with a broader array of high-𝑇 ! polymers, obtained through experimental or computational means, and refining the generalization abilities of ML models. This would potentially enhance both the accuracy and the UQ in predicting the properties of high-𝑇 ! polymers.