Although increasing the σ value increases the score contribution to the loss, it also decreases the prior contribution and thus decreases regularization during optimization. As such, we expect that larger values of σ result in further extrapolation outside the domain of the training set and prior, which is the aspect of the generated molecules we analysed next.