Bottom line: thin shells are not a perfect solution, but if NCS is present, choosing the free set randomly is *never* a better choice, and almost always significantly worse.
hmmm ... I wonder if that is true. For low order NCS (two- three- fold, even five-fold) I don't believe that thin shells are better, since they are a systematic omission of data (whcih can affect maps) and in my experience they do not add much. I have only limited experience on this but I somehow tried both and I seem to have settled with random Rfree. With an NCS axis parallel to a crystallographic one (or when translation NCS is there) that might be a whole different ball game though ... not sure.
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Together with multicopy refinement, randomly chosen test sets were almost certainly a major contributor to the spuriously good Rfree values associated with the retracted MsbA and EmrE structures.
ehm ... I think 16 models systematically displaced along a direction parallel to helix axes contributed much more to that ... as the authors basically said in the original publication if my recollection is not bad.
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