docs: def compute_between_collection_interval_duration(self, prefix):
          """Calculates BETWEEN-collection intervals for the current collection and measure type
              and takes their mean.
  
          :param str prefix: Prefix for the key entry in self.measures.
  
          Negative intervals (for overlapping clusters) are counted as 0 seconds.  Intervals are
          calculated as being the difference between the ending time of the last word in a collection
          and the start time of the first word in the subsequent collection.
  
          Note that these intervals are not necessarily silences, and may include asides, filled
          pauses, words from the examiner, etc.
  
          Adds the following measures to the self.measures dictionary:
              - TIMING_(similarity_measure)_(collection_type)_between_collection_interval_duration_mean:
                  average interval duration separating clusters
  
          """
  
          durations = []  # duration of each collection
          for collection in self.collection_list:
              # Entry, with timing, in timed_response for first word in collection
              start = collection[0].start_time
              # Entry, with timing, in timed_response for last word in collection
              end = collection[-1].end_time
              durations.append((start, end))
  
          # calculation between-duration intervals
          interstices = [durations[i + 1][0] - durations[i][1] for i, d in enumerate(durations[:-1])]
  
          # Replace negative interstices (for overlapping clusters) with
          # interstices of duration 0
          for i, entry in enumerate(interstices):
              if interstices[i] < 0:
                  interstices[i] = 0
  
          self.measures[prefix + 'between_collection_interval_duration_mean'] = get_mean(interstices) \
              if len(interstices) > 0 else 'NA'
  
          if not self.quiet:
              print
              print self.current_similarity_measure + " between-" + self.current_collection_type + " durations"
              table = [(self.current_collection_type + " 1 (start,end)", "Interval",
                        self.current_collection_type + " 2 (start,end)")] + \
                      [(str(d1), str(i1), str(d2)) for d1, i1, d2 in zip(durations[:-1], interstices, durations[1:])]
              print_table(table)
              print
              print "Mean " + self.current_similarity_measure + " between-" + self.current_collection_type + " duration", \
                  self.measures[prefix + 'between_collection_interval_duration_mean']