code: def normalize_score(
      pair2CocitedCnt, paper2cited_list, min_k=10, min_score=0.1
  ):
      res = {}
      for pair, cnt in pair2CocitedCnt.items():
          if (
              pair[0] not in paper2cited_list
              or pair[1] not in paper2cited_list
          ):
              continue
          if (
              len(paper2cited_list[pair[0]]) < min_k
              or len(paper2cited_list[pair[1]]) < min_k
          ):
              continue
          sim = math.sqrt(
              cnt
              * cnt
              / (
                  4
                  * len(paper2cited_list[pair[0]])
                  * len(paper2cited_list[pair[1]])
              )
          )
          if sim > min_score:
              res[pair] = sim
      return res
  
imports: import codecs
  import pickle
  import time
  import os
  from datetime import datetime
  import random
  import numpy
  import math
  from multiprocessing import Process
  from utils.general import *
  from utils.data_helper import *
label_desc: Use image node_id 14 for calling a global function with example usage: normalize_score(pair2CocitedCnt, paper2cited_list, min_k, min_score) and returns: res