docs: def auto_qc(dset,inside_perc=60,atlas=None,p=0.001):
      '''returns ``False`` if ``dset`` fails minimum checks, or returns a float from ``0.0`` to ``100.0`` describing data quality'''
      with nl.notify('Running quality check on %s:' % dset):
          if not os.path.exists(dset):
              nl.notify('Error: cannot find the file!',level=nl.level.error)
              return False
          
          info = nl.dset_info(dset)
          if not info:
              nl.notify('Error: could not read the dataset!',level=nl.level.error)
          
          if any(['stat' in x for x in info.subbricks]):
              with nl.notify('Statistical results detected...'):
                  inside = inside_brain(dset,atlas=atlas,p=p)
                  nl.notify('%.1f significant voxels inside brain')
                  if inside<inside_perc:
                      nl.notify('Warning: below quality threshold!',level=nl.level.warning)
  #                    return False
                  nl.notify('Looks ok')
                  return inside
          
          if len(info.subbricks)>1:
              with nl.notify('Time-series detected...'):
                  return_val = True
                  (cost,overlap) = atlas_overlap(dset)
                  if cost>0.15 or overlap<80:
                      nl.notify('Warning: does not appear to conform to brain dimensions',level=nl.level.warning)
                      return_val = False
                  if len(info.subbricks)>5:
                      (oc,perc_outliers) = outcount(dset)
                      if perc_outliers>0.1:
                          nl.notify('Warning: large amount of outlier time points',level=nl.level.warning)
                          return_val = False
              if return_val:
                  nl.notify('Looks ok')
                  return min(100*(1-cost),overlap,100*perc_outliers)
              return False
          
          with nl.notify('Single brain image detected...'):
              (cost,overlap) = atlas_overlap(dset)
              # Be more lenient if it's not an EPI, cuz who knows what else is in this image
              if cost>0.45 or overlap<70:
                  nl.notify('Warning: does not appear to conform to brain dimensions',level=nl.level.warning)
                  return False
              nl.notify('Looks ok')
              return min(100*(1-cost),overlap)