docstr: Parameters
  ----------
  X : np.array
      Array of word counts, shape (N, 2) where N is the vocab size.  X[:,0] is the
      positive class, while X[:,1] is the negative class. None by default
  
  Returns
  -------
  np.array of p-values
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code: def get_p_vals(self, X):
      """
      Parameters
      ----------
      X : np.array
          Array of word counts, shape (N, 2) where N is the vocab size.  X[:,0] is the
          positive class, while X[:,1] is the negative class. None by default
  
      Returns
      -------
      np.array of p-values
  
      """
      z_scores = self.get_scores(X[:, 0], X[:, 1])
      return norm.cdf(z_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 5 for calling the ScaledFZScore obj's underlying member method code with example usage: obj.get_p_vals(X) and returns: norm