I have to ask flamingly: So what about CC1/2 and CC*? Did we not replace an arbitrary resolution cut-off based on a value of Rmerge with an arbitrary resolution cut-off based on a value of Rmeas already? And now we are going to replace that with an arbitrary resolution cut-off based on a value of CC* or is it CC1/2?
I am asked often: What value of CC1/2 should I cut my resolution at? What should I tell my students? I've got a course coming up and I am sure they will ask me again. Jim ________________________________ From: CCP4 bulletin board [CCP4BB@JISCMAIL.AC.UK] on behalf of Arka Chakraborty [arko.chakrabort...@gmail.com] Sent: Tuesday, August 27, 2013 7:45 AM To: CCP4BB@JISCMAIL.AC.UK Subject: Re: [ccp4bb] Resolution, R factors and data quality Hi all, does this not again bring up the still prevailing adherence to R factors and not a shift to correlation coefficients ( CC1/2 and CC*) ? (as Dr. Phil Evans has indicated).? The way we look at data quality ( by "we" I mean the end users ) needs to be altered, I guess. best, Arka Chakraborty On Tue, Aug 27, 2013 at 9:50 AM, Phil Evans <p...@mrc-lmb.cam.ac.uk<mailto:p...@mrc-lmb.cam.ac.uk>> wrote: The question you should ask yourself is "why would omitting data improve my model?" Phil
