docstr: Return identifiers of models in the ensemble that is best for the 1st metric.
  
  This includes models which have a weight of zero!
  
  Returns
  -------
  list
docstr_tok: ["Return","identifiers","of","models","in","the","ensemble","that","is","best","for","the","1st","metric",".","This","includes","models","which","have","a","weight","of","zero","!","Returns","--","--","--","-","list"]
code: def get_selected_model_identifiers(
      self,
  ) -> list[tuple[int, int, float]]:
      """Return identifiers of models in the ensemble that is best for the 1st metric.
  
      This includes models which have a weight of zero!
  
      Returns
      -------
      list
      """
      return self.pareto_set[0].get_selected_model_identifiers()
  
imports: from __future__ import annotations
  from typing import Sequence
  import warnings
  import numpy
  from sklearn.exceptions import NotFittedError
  from autosklearn.automl_common.common.utils.backend import Backend
  from autosklearn.constants import TASK_TYPES
  from autosklearn.data.validation import SUPPORTED_FEAT_TYPES
  from autosklearn.ensemble_building.run import Run
  from autosklearn.ensembles.abstract_ensemble import AbstractEnsemble, AbstractMultiObjectiveEnsemble
  from autosklearn.ensembles.singlebest_ensemble import SingleModelEnsemble
  from autosklearn.metrics import Scorer, calculate_losses
  from autosklearn.pipeline.base import BasePipeline
  from autosklearn.util.multiobjective import pareto_front
label_desc: Use image node_id 8 for calling the MultiObjectiveDummyEnsemble obj's underlying member method code with example usage: obj.get_selected_model_identifiers() and returns: self