Item 1 would only seem useful when you have sufficient trusted expert ranking to calibrate, but still need to use the votes to extrapolate elsewhere [...]

Exactly. Remember, the whole point of this procedure is to tweak how much credibility you give to voters as a function of the number of voters you have - the only reason I mention experts is that they bypass the sample size problem.

(and where you expect trusted experts to align with your audience - if experts routinely downvote dark ales, and your audience prefers them, you're going to get a wonky heuristic)

Okay, that's a problem. I think it falls as a subset of the earlier problem of finding trusted expert rankings, however.

Item 2 strikes me as clever and ideal, but I'd think you'd need quite a lot of data before you'd be able to actually calibrate that. So you're stuck using 0.05 until you have quite a lot of data.

If you don't have a lot of data, you're not going to have much to offer your users anyway.