code: def _fit_and_score_fold(
      est, x, y, scorer, train_index, test_index, fit_params, idx, fold
  ):
      score = _fit_and_score(
          est,
          x,
          y,
          scorer,
          train_index,
          test_index,
          est.get_params(),
          fit_params,
          {},
      )
      return idx, fold, score, est
  
imports: import numbers
  from joblib import Parallel, delayed
  import numpy
  from scipy.stats import kendalltau, rankdata, spearmanr
  from sklearn.base import BaseEstimator, clone
  from sklearn.model_selection import check_cv
  from sklearn.utils._param_validation import Interval, StrOptions
  from .base import _fit_and_score
  from .stacking import Stacking
label_desc: Use image node_id 2 for calling a global function with example usage: _fit_and_score_fold(est, x, y, scorer, train_index, test_index, fit_params, idx, fold) and returns: idx,  fold,  score,  est