I actually got the link to his code yesterday and it's eerily close to what I wrote a few months ago, but I rejected that approach because I didn't like that any of the numbers in [0.5,1.0) were so much more likely to be returned than 0.0. This gives the highest possible entropy and all numbers representable by floating points in that range can be returned, but the trade-off is that certain values will be returned vastly much more often than others. It's this discussion of trade-offs that I'm actually missing.

I don't feel competent enough to write that paper/article/rant about the trade-offs myself, I barely understand math and randomness, but I'm getting tired of all the libraries out there that say "uniform[1] random[2] floating points[3] [1] - not actually uniform [2] - not actually random [3] - terms and conditions apply, YMMV, not valid where invalid".