On Wed, Nov 03, 2021 at 12:54:00PM +0000, Ian Tickle wrote:
> Suppose you had to compare two datasets differing only in their
> high-resolution cut-offs. Now Rwork, Rfree and Rall will inevitably have
> higher values at the high d* end, which means that if you apply a cut-off
> at the high d* end all the overall R values will get smaller, so use of any
> R value as a data-quality metric will tend to result in selection of the
> lowest-resolution dataset from your candidate set, which may well give a lower
> quality map: not what you want!
Couldn't that be avoided by using the common set of reflection data
present in both the A and B dataset (from David's example - or even
across a whole series A-Z)? When at the same time we keep the same
model parametrisation (i.e. not adding altConfs or waters, keeping
same TLS definitions etc) it might be useful to compare different data
processing procedures via the R{free,all,work} during refinement.
As far as I can see, the only difference would be the actual values of
F and sig(F) (or I and sig(I)) attached to the identical set of Miller
indices ... right?
Cheers
Clemens
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