def METHOD_NAME(
    cls,
    metric: MetricConfiguration,
    configuration: Optional[ExpectationConfiguration] = None,
    execution_engine: Optional[ExecutionEngine] = None,
    runtime_configuration: Optional[dict] = None,
):
    """Returns a dictionary of given metric names and their corresponding configuration, specifying the metric
    types and their respective domains"""
    dependencies: dict = super().METHOD_NAME(
        metric=metric,
        configuration=configuration,
        execution_engine=execution_engine,
        runtime_configuration=runtime_configuration,
    )
    if (
        metric.metric_name
        == f"column_values.z_score.under_threshold.{MetricPartialFunctionTypeSuffixes.CONDITION.value}"
    ):
        dependencies[
            f"column_values.z_score.{MetricPartialFunctionTypeSuffixes.MAP.value}"
        ] = MetricConfiguration(
            metric_name=f"column_values.z_score.{MetricPartialFunctionTypeSuffixes.MAP.value}",
            metric_domain_kwargs=metric.metric_domain_kwargs,
        )
    if (
        metric.metric_name
        == f"column_values.z_score.{MetricPartialFunctionTypeSuffixes.MAP.value}"
    ):
        dependencies["column.mean"] = MetricConfiguration(
            metric_name="column.mean",
            metric_domain_kwargs=metric.metric_domain_kwargs,
        )
        dependencies["column.standard_deviation"] = MetricConfiguration(
            metric_name="column.standard_deviation",
            metric_domain_kwargs=metric.metric_domain_kwargs,
        )
    return dependencies