code: def MCST(**kwargs):
      """MCST class for Monte Carlo Shapiro Tests thresholder.
  
      Use uniform random sampling and statstical testing to evaluate a
      non-parametric means to threshold scores generated by the decision_scores
      where outliers are set to any value beyond the minimum value left after
      iterative Shapiro-Wilk tests have occured. Note** accuracy decreases with
      array size. For good results the should be array<1000. However still this
      threshold method may fail at any array size.
  
      Parameters
      ----------
  
      random_state : int, optional (default=1234)
           Random seed for the uniform distribution. Can also be set to None.
  
      """
  
      from pythresh.thresholds.mcst import MCST as MCST_thres
  
      return MCST_thres(**kwargs)
  
label_desc: Use image node_id 18 for calling a global function with example usage: MCST() and returns: MCST_thres