If AIMLESS is throwing out a lot of reflections, something is wrong. You should 
look closely at what is being rejected, in the list of “ROGUES” and the plot of 
position of outliers on the detector face

DIALS (probably dials.scale) has its own rejection scheme, as does XDS

There are two basic reasons for rejecting reflections 
1) they belong to part of the data collection where all data are unreliable, eg 
because of radiation damage
2) individual reflections which are “wrong” for some other reason, ice spots, 
detector defects, multiple lattices etc

There should never be “a lot” of outliers in category 2

Phil

> On 1 Oct 2022, at 13:02, Matt McLeod <mjmcleo...@gmail.com> wrote:
> 
> Hey everyone,
> 
> Thanks for all the suggestions there are a few different things I can try 
> now.  The data is very aniosotropic (STARANISO might help) in regards to how 
> the crystal diffracts and I think changing the bin size will help 
> specifically with PAIREF (its an warning so it completes the run).   I 
> collected the data using oil and at room temperature using a vector scan so 
> there are also differences in data quality through the collection (not too 
> severe based on data processing), radiation damage, a changing background 
> from oil, etc.  
> 
> However, diagnosing the problem further it seems that merging with AIMLESS 
> throws a lot of my high resolution reflections out...like alot.  This 
> explains why truncating the data doesnt change the maps and explains why my 
> table 1 statistics for high resolution bin are dismal.  I can supply log 
> files when I find them.  Now I have to determine if the outlier rejections 
> are useful or not and why DIALS processing didn't flag these as rejections.
> 
> I have yet to look into AIMLESS rejection outlier protocol but I would guess 
> that the reflections are real at high resolution but there are not that many 
> of them and they are not that redundant and therefore are being tossed.
> 
> Matt
> 
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