Check your mosflm input file. 

If this is an "ADSC" type detector and you have specified that it is 
(using "DETECTOR TYPE ADSC" or "SCANNER TYPE ADSC"), but have not 
explicitly specified the overload limit with "OVERLOAD CUTOFF", then the 
default overload cutoff for integration will be 100,000, and this 
effectively turns off overload detection.  Note that there are TWO 
different overload cutoffs in mosflm, but both are listed in the log 
next to the string "(CUTOFF)".

I only discovered this myself a few weeks ago, and I have patched the 
current Elves release:
http://bl831.als.lbl.gov/~jamesh/elves/download.html
 to avoid this problem when they run mosflm, but versions from the last 
two years may actually miss overloads!

-James Holton
MAD Scientist

Simon Kolstoe wrote:
> Thanks Tim, Phil and Andrew for your answers.
>
> Just one further related question:
>
> Why is it that mosflm seems to report higher completeness than XDS on 
> the same data (I've seen this on about 50 datasets)? I always thought 
> it was due to mosflms peak extrapolation but it seems this isn't the 
> answer if SCALA throws those reflections out.
>
> Thanks,
>
> Simon
>
> On 7 Jun 2010, at 15:35, Phil Evans wrote:
>
>> Mosflm integrates them (profile-fitted overloads) but flags them. 
>> Pointless uses them for systematic absence tests. Scala by default 
>> ignores them, but you can include them if you want: this is not 
>> normally recommended since they are pretty inaccurate (look in the 
>> "Excluded data" tab of ccp4i/Scala)
>>
>> If you are merging strong & weak datasets it should do the right 
>> thing, I think.
>>
>> Phil
>>
>>
>> On 7 Jun 2010, at 15:09, Simon Kolstoe wrote:
>>
>>> Dear CCP4bb,
>>>
>>> I was wondering if someone could tell me how mosflm and scala deal 
>>> with overloaded reflections. From my understanding mosflm 
>>> extrapolates the overloaded peaks but then scala throws them out 
>>> completely - is this right?
>>>
>>> If so am I right to not worry about "contamination" from 
>>> extrapolated peaks when combining high and low resolution datasets 
>>> from the same crystal?
>>>
>>> Thanks
>>>
>>> Simon