There are structured approaches to delphi groups which incorporate bayes rules and insights around the psychology of eliciting and structuring expert judgement that you could mimic.

Yes, the technology I'm using (prediction polls) are essentially this. It's Delphi groups weighted by Brier scores. The paper I link to above compares them to a prediction market with the same questions - with proper extremizing algorithms, the prediction poll actually does better (especially early on).

The reason I came up with this solution is that I wanted to use prediction markets for a specific class of impact assesments, but they weren't suited for the task. Prediction markets require either a group of interested suckers to take the bad bets, or a market maker who is sufficiently interested in the outcome to be willing to take the bad side on ALL the sucker bets. My solution complements prediction markets by being much better in those cases by avoiding the zero sum game, and instead just directly paying experts for their expertise.