Then, we created a mixture model to aggregate the welfare range distributions across all models to factor in our uncertainty about which model is correct. Specifically, for a given organism and model, we modeled each distribution as a normal distribution with a 90% interval with lower and upper bounds equal to the fifth- and ninety-fifth percentile welfare ranges. Each of the eight models was assigned an equal probability of being correct. Then, we sampled 10,000 welfare ranges from this mixture model and stored the resulting 5th-, 50th-, and 95th-percentile welfare ranges in a data frame.
I think you aggregated them with the mean.