code: def incorrect_flipped_recall_wilson(y_true, y_pred):
      bounds = recall_wilson(y_true, y_pred)
      return np.array([bounds[1], bounds[0]])
  
imports: import matplotlib
  import matplotlib.pyplot
  import numpy
  import pytest
  from sklearn.metrics import accuracy_score, confusion_matrix, recall_score
  from sklearn.utils import check_consistent_length
  from fairlearn.experimental.enable_metric_frame_plotting import plot_metric_frame
  from fairlearn.metrics import MetricFrame
  from fairlearn.metrics._plotter import _CONF_INTERVALS_FLIPPED_BOUNDS_ERROR, _CONF_INTERVALS_MUST_BE_ARRAY, _METRIC_FRAME_INVALID_ERROR
  from .data_for_test import g_1, y_p, y_t
label_desc: Use image node_id 4 for calling a global function with example usage: incorrect_flipped_recall_wilson(y_true, y_pred) and returns: np