code: def score_cindex(est, X_test, y_test, **predict_params):
      prediction = est.predict(X_test, **predict_params)
  
      res = concordance_index_censored(
          y_test["fstat"], y_test["lenfol"], prediction
      )
      return res[0]
  
imports: import numpy
  from numpy.testing import assert_array_equal
  import pytest
  from sklearn.dummy import DummyRegressor
  from sklearn.metrics import mean_squared_error
  from sklearn.model_selection import KFold, ParameterGrid
  from sksurv.ensemble import ComponentwiseGradientBoostingSurvivalAnalysis
  from sksurv.kernels import ClinicalKernelTransform
  from sksurv.linear_model import IPCRidge
  from sksurv.meta import EnsembleSelection, EnsembleSelectionRegressor
  from sksurv.metrics import concordance_index_censored
  from sksurv.svm import FastKernelSurvivalSVM, FastSurvivalSVM
  from sksurv.testing import FixtureParameterFactory, assert_cindex_almost_equal
  from sksurv.tree import SurvivalTree
  from sksurv.util import check_array_survival
label_desc: Use image node_id 1 for calling a global function with example usage: score_cindex(est, X_test, y_test) and returns: res