Apart from experimental data, the creation of large amounts of in-silico data is possible with sufficient computational resources . While this approach is useful in cases where the experimental determination is challenging, some experimental properties, like the reaction yield, remain elusive to be reliably computed due to the myriad of factors (side-reactions, impurities, solvation effects, interface effects,...) that influence this observable . Another pitfall regarding computational data is its accuracy with respect to the ground truth, in particular for multiple factors relevant throughout catalysis, such as non-covalent interactions (NCIs) for organocatalysis or spin properties for transition metal catalysis . While most quantities can in principle be computed with the highest accuracy using advanced tools, the associated computational cost needs to be considered .