The rigid-body target refits the scale at every evaluation, deliberately - held fixed, the target
would measure the scale as much as the placement, and the body would translate to repair a scale
error instead of moving to where the density is. That refit was gemmi's unbounded fit, the one
already replaced for the reported scale, and here it was worse: measured over a corpus of
deposited models, 40% of the evaluations that decide where the model goes came out with a b_sol
outside 10-80 A^2, on 57 of 89 datasets, ranging from -8072 to +1721. A negative b_sol is a
solvent term that GROWS with resolution. One crystal ran its entire committed placement between
290 and 430 A^2, and that placement went into the reported maps.
The bulk solvent is fitted once per zone instead, inside the same physical box the reported fit
searches, and then held while the overall scale and the anisotropic B keep following the body.
That split is the point: k_sol and b_sol describe the crystal's disordered solvent, not the fit of
one placement, and measured across a whole zone they drift by a single grid step. Fitting them at
every evaluation costs three times the wall clock, makes the scaler 82% of the run, and moves
discontinuously under a forward difference - which is poison for a numerical Jacobian. This costs
4%, leaves no evaluation outside the box, and lands the body within 0.37 degrees of the expensive
version, against 4.33 degrees for what it replaces.
Placements change on fourteen crystals in eighty-nine. R-free is a wash on the mean; the step
buys more total R-free from fewer commits, and the gain sits where the runaway actually bit.
Two things found while auditing the file and left as they were, because they are right: the
refinement sees working reflections only, end to end, and the gauge that removes the origin-free
directions of a polar group carries more than half the whole refined translation in ninety-four
of a hundred and thirty-nine polar zones. It had no test. It has one now.
An observation with no calculated amplitude gets a zero residual, which drops it from the target
rather than scoring it as a perfect fit, and is now counted and reported - a large count says the
model's reflection conditions do not match the data's, which is a statement about the model.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EFEJG6WBQv8th4UJFNe53N
leonarski_fandClaude Opus 5
e5c96cd41b
