     isModified: default_value is actual_value
 
 
-  getThresholdsAndCriteria = (model) ->
-    if criterionTable = _.inspect 'output - training_metrics - Maximum Metrics', _model
+  getThresholdsAndCriteria = (model, tableName) ->
+    if criterionTable = _.inspect tableName, _model
 
       # Threshold dropdown items
       thresholdVector = table.schema.threshold


    when 'deeplearning'
      if table = _.inspect 'output - training_metrics - Metrics for Thresholds', _model
        renderPlot 'ROC Curve - Training Metrics', no, _.plot (g) ->
          g(
            g.path g.position 'fpr', 'tpr'
            g.line(
              g.position (g.value 1), (g.value 0)
              g.strokeColor g.value 'red'
            )
            g.from table
            g.domainX_HACK 0, 1
            g.domainY_HACK 0, 1
          )

      if table = _.inspect 'output - validation_metrics - Metrics for Thresholds', _model
        renderPlot 'ROC Curve - Validation Metrics', no, _.plot (g) ->
          g(
            g.path g.position 'fpr', 'tpr'
            g.line(
              g.position (g.value 1), (g.value 0)
              g.strokeColor g.value 'red'
            )
            g.from table
            g.domainX_HACK 0, 1
            g.domainY_HACK 0, 1
          )

      if table = _.inspect 'output - Variable Importances', _model
        renderPlot 'Variable Importances', no, _.plot (g) ->


    when 'glm'
      if table = _.inspect 'output - training_metrics - Metrics for Thresholds', _model
        plotter = _.plot (g) ->
          g(
            g.path g.position 'fpr', 'tpr'
            g.line(
              g.position (g.value 1), (g.value 0)
              g.strokeColor g.value 'red'
            )
            g.from table
            g.domainX_HACK 0, 1
            g.domainY_HACK 0, 1
          )
        # TODO Mega-hack alert. Last arg thresholdsAndCriteria applicable only to ROC charts for binomial models.
        renderPlot 'ROC Curve - Training Metrics', no, plotter, getThresholdsAndCriteria _model, 'output - training_metrics - Maximum Metrics'

      if table = _.inspect 'output - validation_metrics - Metrics for Thresholds', _model
        plotter = _.plot (g) ->
          g(
            g.path g.position 'fpr', 'tpr'
            g.line(
              g.position (g.value 1), (g.value 0)
              g.strokeColor g.value 'red'
            )
            g.from table
            g.domainX_HACK 0, 1
            g.domainY_HACK 0, 1
          )
        # TODO Mega-hack alert. Last arg thresholdsAndCriteria applicable only to ROC charts for binomial models.
        renderPlot 'ROC Curve - Validation Metrics', no, plotter, getThresholdsAndCriteria _model, 'output - validation_metrics - Maximum Metrics'

      if table = _.inspect 'output - Standardized Coefficient Magnitudes', _model
        renderPlot 'Standardized Coefficient Magnitudes', no, _.plot (g) ->
