code: def identify_mediation_second_stage_confounders(
      graph: nx.DiGraph,
      action_nodes: List[str],
      mediator_nodes: List[str],
      outcome_nodes: List[str],
      observed_nodes: List[str],
      backdoor_adjustment: BackdoorAdjustment,
  ):
      # Create estimands dict as per the API for backdoor, but do not return it
      estimands_dict = {}
      backdoor_sets = identify_backdoor(
          graph,
          mediator_nodes,
          outcome_nodes,
          observed_nodes,
          backdoor_adjustment,
      )
      (
          estimands_dict,
          backdoor_variables_dict,
      ) = build_backdoor_estimands_dict(
          mediator_nodes,
          outcome_nodes,
          observed_nodes,
          backdoor_sets,
          estimands_dict,
      )
      # Setting default "backdoor" identification adjustment set
      default_backdoor_id = get_default_backdoor_set_id(
          graph, action_nodes, outcome_nodes, backdoor_variables_dict
      )
      estimands_dict["backdoor"] = estimands_dict.get(
          str(default_backdoor_id), None
      )
      backdoor_variables_dict["backdoor"] = backdoor_variables_dict.get(
          str(default_backdoor_id), None
      )
      return backdoor_variables_dict
  
imports: import itertools
  import logging
  from enum import Enum
  from typing import Dict, List, Optional, Union
  import networkx
  import sympy
  import sympy.stats
  from dowhy.causal_identifier.efficient_backdoor import EfficientBackdoor
  from dowhy.causal_identifier.identified_estimand import IdentifiedEstimand
  from dowhy.graph import check_dseparation, check_valid_backdoor_set, check_valid_frontdoor_set, check_valid_mediation_set, do_surgery, get_all_directed_paths, get_backdoor_paths, get_descendants, get_instruments, has_directed_path
  from dowhy.utils.api import parse_state
label_desc: Use image node_id 14 for calling a global function with example usage: identify_mediation_second_stage_confounders(graph, action_nodes, mediator_nodes, outcome_nodes, observed_nodes, backdoor_adjustment) and returns: backdoor_variables_dict