I've also experienced this, but since the improvement is small, I did not pay much attention, and did not investigate. My hypothesis why this occurs agrees with yours. Nothing should prevent you to make use of this effect! best, Kay
On Mon, 20 Feb 2017 08:24:58 -0300, Jorge Iulek <[email protected]> wrote: ><html> > <head> > <meta http-equiv="content-type" content="text/html; > charset=ISO-8859-1"> > </head> > <body text="#000000" bgcolor="#FFFFFF"> > <font size="+1"><font face="Times New Roman, Times, serif">Dear all,<br> > <br> > I have been noticing, with many datasets, processed > the duet > xds/scale, that when one integrates to a resolution limit which > is (a little) higher than the one used for scaling/merging, the > statistics (and here I mean R-symm, R-meas, <I/sigI> and > even CC1//2) get better (I might also advance that, in many > cases, completeness gets a little better too).<br> > Just to make clear, suppose I want to process to > resolution > x (according to any criteria/index I decide) ; suppose y is a > little (how much is yet another good discussion) higher > resolution, id est, numerically, x > y, I get better > statistics when I integrate up to y and scale/merge to x, rather > than using x in both cases, therefore, its seems to be advisable > to integrate up to y and then to scale/merge up to x. <br> > So the question is: why does this happen? Would > this be > related this the fact that the spot profiles gets more well > defined? In this case, is it fair to do this and to obtain > better data (and, I suppose, a better structural model)? In > principle, I suppose this might be legitimate, as even CC1/2 > gets better. Has anyone else ever observed such behavior, maybe > with other processing duets? <br> > <br> > Jorge<br> > </font></font> > </body> ></html>
