Assessing the quality of uncertainty in ML is difficult because it depends on the methods used, and there is no clear standard for what uncertainty should look like. Additionally, there isn't a single metric that fits all ML tasks for measuring this quality. In our work, we use three specific metrics to thoroughly evaluate how well uncertainty is quantified in predicting 𝑇 ! values for polymers.