For multi-structure images, we evaluated only a smaller fraction of structure predictions due to an overall poor prediction (Table ). The precision was calculated as follows -for example, if three structures were correctly predicted from a total number of six predicted structures from such an image the precision is 50%. If only five out of 6 structures were predicted, the missing was counted as a false negative. Among tested OCSR tools OCMR and SwinOCSR programs show the lowest metrics for multi-structure images and will not be discussed further (see the supplementary material). If better results will be obtained for such multi structure image modalities in the future, a more in depth quality assessment is indicated. 103 randomly selected reaction images were selected that contained 284 reactions or reaction steps in total for evaluating the quality of predicting reactions. To compare predictions from OSRA, RxnScribe, and ReactionDataExtractor we have disregarded the output of all three programs for reaction reagents that are typically shown above or below the reaction arrow -these are often a mixture of text and chemical structure images. Thus, although not qualifying the correctness of such reagent extraction, both RxnScribe and ReactionDataExtractor were found to be able to extract more reagents than OSRA could. The approach to obtain TP, FP, and FN value for reactions has been the same as for the single molecule images. It is interesting to note that RxnScribe has predicted more than 284 reactions; this seems to happen as any detected arrow is generally predicted as a chemical reaction. The respective quality control files for tables 1-3 are found in the supplementary material.