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We don't currently have a really good measure of that point where adding the extra shell of data adds "significant" information (whatever that means. However, my rough trials (see http://www.ncbi.nlm.nih.gov/pubmed/23793146) suggested that the exact cutoff point was not very critical, presumably as the "information content" fades out slowly, so it probably isn't something to agonise over too much. K & D's paired refinement may be useful though.

I would again caution against looking too hard at CC* rather than CC1/2: they are exactly equivalent, but CC* changes very rapidly at small values, which may be misleading. The purpose of CC* is for comparison with CCcryst (i.e. Fo to Fc).

I would remind any users of Scala who want to look back at old log files to see the statistics for the outer shell at the cutoff they used, that CC1/2 has been calculated in Scala for many years under the name CC_IMEAN. It's now called CC1/2 in Aimless (and Scala) following Kai's excellent suggestion.

Phil


On 28 Aug 2013, at 08:21, Bernhard Rupp <[log in to unmask]> wrote:

> >Based on the simulations I've done the data should be "cut" at CC1/2 = 0. Seriously. Problem is figuring out where it hits zero. 
>  
> But the real objective is – where do data stop making an improvement to the model. The categorical statement that all data is good
> is simply not true in practice. It is probably specific to each data set & refinement, and as long as we do not always run paired refinement ala KD
> or similar in order to find out where that point is, the yearning for a simple number will not stop (although I believe automation will make the KD approach or similar eventually routine).
>  
> >As for the "resolution of the structure" I'd say call that where |Fo-Fc| (error in the map) becomes comparable to Sigma(Fo). This is I/Sigma = 2.5 if Rcryst is 20%.  That is: |Fo-Fc| / Fo = 0.2, which implies |Io-Ic|/Io = 0.4 or Io/|Io-Ic| = Io/sigma(Io) = 2.5.
>  
> Makes sense to me...
>  
> As long as it is understood that this ‘model resolution value’ derived via your argument from I/sigI is not the same as a <I/sigI> data cutoff (and that Rcryst and Rmerge have nothing in common)….
>  
> -James Holton
> MAD Scientist
>  
> 
> Best, BR
> 
>  
> 
>  
> 
> 
> On Aug 27, 2013, at 5:29 PM, Jim Pflugrath <[log in to unmask]> wrote:
> 
> 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 [[log in to unmask]] on behalf of Arka Chakraborty [[log in to unmask]]
> Sent: Tuesday, August 27, 2013 7:45 AM
> To: [log in to unmask]
> 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 <[log in to unmask]> wrote:
> The question you should ask yourself is "why would omitting data improve my model?"
> 
> Phil