Repeated runs, on average, appear to have little benefit, as the average MAE and RMSE decrease only moderately, and the average R 2 increases only slightly, when increasing the batch size from 1 to 10 replicates for all protocols. However, one can see in Figure that the spread of the MAE, RMSE, and R 2 distributions significantly decrease with increasing batch size, meaning the likelihood of calculating a set of particularly poor (or outstanding) RBFEs decreases with repeated runs. This tradeoff should be considered when planning a high-throughput RBFE campaign: if one can accept a higher variance of calculations, then significantly more mutations can be explored at a similar cost.