Both sources of irreducible error were observed in the RGD1 dataset and are expected to be found in any other computational dataset of conformationally complex reactants without explicit protocols for mitigation. Although these errors are "irreducible" from the perspective of performance in the G2Ea task for a given dataset, they are reducible from the perspective of curating better datasets. For example, there are many possibilities for developing better filters for unintended transition states-from more complex models to using more informative featurizations for the unintended/intended classification task-but they have yet to be implemented. We estimated that the majority of prediction outliers in the current study were in fact unintended reactions and that perfect filtering would reduce the irreducible error for the G2Ea task by ∼ 1 -2 kcal/mol with the remaining ∼ 2 -3 kcal/mol being accounted for by incomplete conformational sampling.