We leveraged Summit to build the predictive models from the literature reports. As shown in Figure , we utilized the ExperimentalEmulator feature in Summit, which creates a benchmark based on experimental data. The regressor used was a neural network with one hidden layer of 512 units with a ReLu activation function. A one-hot encoding was used for the pre-catalyst and ligand combinations. The neural networks were trained by five-fold cross validation over 1000 epochs using stochastic gradient descent. Figures show the parity plots for the benchmarks.