To assess the model, a series of real-world scenarios were identified. One scenario was to split the data, so the last chronological run was the test data, and the previous runs were the training data. This corresponds to the training data that would exist whilst the final reaction was being performed. The trend of the results from this use case closely align with those from cross-validation (Figure in the Supplementary Information). Compared to the crossvalidation, the model performed slightly better for all values of z greater than zero.