Translates a Bayesian multilevel model fitted with brms into a
nested-plate UMG. The random-effect structure is parsed from the
model formula with the same engine as umg_from_lmer(), and the
fixed-effect population parameters are rendered in their
prior-closed (Bayesian) form, consistent with the article's
treatment of priors as parameter promotion.