code: def get_eidos_scorer():
      
      table = load_eidos_curation_table()
  
      # Get the overall precision
      total_num = table['COUNT of RULE'].sum()
      weighted_sum = table['COUNT of RULE'].dot(table['% correct'])
      precision = weighted_sum / total_num
      # We have to divide this into a random and systematic component, for now
      # in an ad-hoc manner
      syst_error = 0.05
      rand_error = 1 - precision - syst_error
      prior_probs = {'rand': {'eidos': rand_error}, 'syst': {'eidos': syst_error}}
  
      # Get a dict of rule-specific errors.
      subtype_probs = {'eidos':
                       {k: 1.0-min(v, 0.95)-syst_error for k, v
                        in zip(table['RULE'], table['% correct'])}}
      scorer = SimpleScorer(prior_probs, subtype_probs)
      return scorer
docs: Return a SimpleScorer based on Eidos curated precision estimates.