code: def _make_label(
      mean: float,
      sem: float,
      name: str,
      is_relative: bool,
      Z: Optional[float],
  ) -> str:
      estimate = str(round(mean, DECIMALS))
      perc = "%" if is_relative else ""
      ci = (
          ""
          if (Z is None or np.isnan(sem))
          else _format_CI(
              estimate=mean, sd=sem, relative=is_relative, zval=Z
          )
      )
      return f"{name}: {estimate}{perc} {ci}<br>"
  
imports: import warnings
  from typing import Dict, Iterable, List, Optional, Tuple, Union
  import numpy
  import pandas
  import plotly.graph_objs
  from ax.core.experiment import Experiment
  from ax.core.objective import MultiObjective
  from ax.core.optimization_config import MultiObjectiveOptimizationConfig, OptimizationConfig
  from ax.core.outcome_constraint import ObjectiveThreshold
  from ax.exceptions.core import UserInputError
  from ax.plot.base import AxPlotConfig, AxPlotTypes, CI_OPACITY, DECIMALS
  from ax.plot.color import COLORS, DISCRETE_COLOR_SCALE, rgba
  from ax.plot.helper import _format_CI, _format_dict, extend_range
  from ax.plot.pareto_utils import ParetoFrontierResults
  from ax.service.utils.best_point_mixin import BestPointMixin
  from ax.utils.common.typeutils import checked_cast, not_none
  from plotly import express
  from scipy.stats import norm
label_desc: Use image node_id 1 for calling a global function with example usage: _make_label(mean, sem, name, is_relative, Z) and returns: name, str, estimate, perc, str, ci, str