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I tested locally at JLab ifarm with the steering file: PhysicsRun2019_pass1_recon_skimmed.lcsim on an evio. I got the data_events_mollerskim.slcio and data_events_v0skim.slcio in addition to the unskimmed data_events.slcio and the DQM root file: data_events_data_quality_plots.root. So I think it will also work for large scale swif2 job submission.
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Implement Moller skimming, largely based on the V0 skimmer and adapted to Moller selection.
Local testing yields a filter efficiency of 2.4%: