code: def _weighted_h_mean(self, precision_normcdf, recall_normcdf):
      scores = (
          (1 + self.beta_**2)
          * (precision_normcdf * recall_normcdf)
          / ((self.beta_**2) * precision_normcdf + recall_normcdf)
      )
      return scores
  
imports: from abc import ABC, abstractmethod
  import numpy
  import pandas
  from scipy.stats import norm, rankdata
  from scattertext.Common import DEFAULT_SCALER_ALGO, DEFAULT_BETA
label_desc: Use image node_id 6 for calling the ScaledFScorePresets obj's underlying member method code with example usage: obj._weighted_h_mean(precision_normcdf, recall_normcdf) and returns: scores