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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_biased_correlations(data, threshold= 10):
 """ Gets the highest few correlations for each bit, across the entirety of the data. Meant to provide a comparison point for the pairwise correlations reported in the literature, which are typically between neighboring neurons tuned to the same inputs. We would expect these neurons to be among the most correlated in any region, so pairwise correlations between most likely do not provide an unbiased estimator of correlations between arbitrary neurons. """

  data = data.toDense()
  correlations = numpy.corrcoef(data, rowvar = False)
  highest_correlations = []
  for row in correlations:
    highest_correlations += sorted(row, reverse = True)[1:threshold+1]
  return numpy.mean(highest_correlations)