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Thermostability predictions are generated based on a number of structural, residue and alignment features for a given protein. We use a gradient boosting model trained to predict the thermostability to deliver the probability variants to 3DM. The thermostability prediction value indicates how likely it is that a given variant results in a net positive ΔΔG value, thus resulting in a more stable protein on the whole.