code: def _get_scaled_f_score_from_counts(
      cat_word_counts,
      not_cat_word_counts,
      scaler_algo,
      beta=DEFAULT_BETA,
  ):
      p_word_given_category = (
          cat_word_counts.astype(np.float) / cat_word_counts.sum()
      )
      p_category_given_word = (
          cat_word_counts
          * 1.0
          / (cat_word_counts + not_cat_word_counts)
      )
      scores = ScaledFScore._get_harmonic_mean_of_probabilities_over_non_zero_in_category_count_terms(
          cat_word_counts,
          p_category_given_word,
          p_word_given_category,
          scaler_algo,
          beta,
      )
      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 4 for calling the ScaledFScore obj's underlying member method code with example usage: obj._get_scaled_f_score_from_counts(cat_word_counts, not_cat_word_counts, scaler_algo, beta) and returns: scores