code: def scoring_method(
      self,
  ) -> Union[None, ScoringMethod, Dict[str, ScoringMethod]]:
      methods: Dict[str, ScoringMethod] = {}
  
      if self.epistemic_enabled:
          methods[f"{self.name}_epistemic"] = CVATEpistemicScoring(
              top_k=int(self.conf.get("epistemic_top_k", "10")),
              infer_task=lib.infers.ToolTracking(
                  self.bundle_path,
                  self.conf,
                  dropout=0.2,
                  train_mode=True,
                  skip_writer=True,
              ),
              function="monailabel.endoscopy.tooltracking",
              max_samples=self.epistemic_max_samples,
              simulation_size=self.epistemic_simulation_size,
              use_variance=True,
          )
      return methods
  
imports: import logging
  import os
  from typing import Any, Dict, Optional, Union
  import lib.infers
  import lib.trainers
  from lib.scoring.cvat import CVATEpistemicScoring
  from monai.bundle import download
  from monailabel.config import settings
  from monailabel.interfaces.config import TaskConfig
  from monailabel.interfaces.tasks.infer_v2 import InferTask
  from monailabel.interfaces.tasks.scoring import ScoringMethod
  from monailabel.interfaces.tasks.strategy import Strategy
  from monailabel.interfaces.tasks.train import TrainTask
  from monailabel.tasks.activelearning.epistemic import Epistemic
  from monailabel.utils.others.generic import strtobool
label_desc: Use image node_id 5 for calling the ToolTracking obj's underlying member method code with example usage: obj.scoring_method() and returns: methods