Comment on UQ by Gareth Williams

You can average over a series of real-world measurements. Assuming they are independent and drawn from some probability distribution, the average is better than any one measurement.
You can also average over many runs of a model with randomly drawn parameters (that is a Monte-Carlo simulation).
But it makes no sense at all to average over a number of different models that make fundamentally different assumptions. There is no statistical reason (Bayesian or otherwise) to think that will give a better answer than any one of them. If one of them happened to be right, you are just averaging it with wrong answers.