What's the theoretical basis for using llm consensus as a probability estimator for real world events [R]

This is a genuine technical question here. I've been looking at systems that use an ensemble of ai models to generate probability estimates for open ended real world events. The claim is that consensus across multiple models produces more calibrated estimates than any single model. this makes sense