For integration with experiments, one could imagine a 'meta-decision-tree' or a Bayesian algorithm in conjunction with an automated characterization probe in real time, scanning energy ranges with high expected information value until sufficient signal is achieved to determine structural properties of interest with reasonably high accuracy, analogously to an active learning loop as used in other contexts for ML and materials science .