code: def sensitivity_score(
      y_true, y_pred, pos_label=1, sample_weight=None
  ):
      """Alias of :func:`sklearn.metrics.recall_score` for binary classes only."""
      return recall_score(
          y_true,
          y_pred,
          pos_label=pos_label,
          sample_weight=sample_weight,
      )
  
imports: from itertools import permutations
  from typing import Union
  import warnings
  import numpy
  import pandas
  from scipy.special import rel_entr
  from sklearn.metrics import make_scorer, recall_score, precision_score
  from sklearn.metrics import multilabel_confusion_matrix
  from sklearn.metrics._classification import _prf_divide, _check_zero_division
  from sklearn.neighbors import NearestNeighbors
  from sklearn.utils import check_X_y
  from aif360.metrics import ot_metric
  from aif360.sklearn.utils import check_inputs, check_groups
  from aif360.detectors.mdss.ScoringFunctions import BerkJones, Bernoulli
  from aif360.detectors.mdss.MDSS import MDSS
label_desc: Use image node_id 35 for calling a global function with example usage: sensitivity_score(y_true, y_pred, pos_label, sample_weight) and returns: recall_score