EcoService Models Library (ESML)

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Variables Details

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EM Identity and Description

EM ID variable.detail.emIdHelp ?	EM-857
Document Author variable.detail.emDocumentAuthorHelp ?	Warren Pinnacle Consulting, Inc.
Document Year variable.detail.emDocumentYearHelp ?	2016

Variable General Info

Name variable.detail.varNameHelp ?	Change in wetland type ? Comment: Map distributions of wetlands are predicted under conditions of accelerated sea level rise, and results are summarized in tabular and graphical form. For each time step the fractional conversion from one class to another is computed on the basis of the relative change in elevation divided by the elevation range of the class in that cell. In addition to mapped output: Available Statistics include: • n cells: The number of cells covered by that land category. Statistics based on small sample sizes should probably be discounted to some degree. • 5th percentile and 95th percentile: The 90% confidence interval for this particular land category in half-tide units. These can be compared with the “Min HTU” and “Max HTU” conceptual model columns. • Mean, St. Dev.: The average elevation value and standard deviation in half tide units. • Min, Max: The minimum and maximum elevation for this cell in half-tide units. These data are usually less useful as horizontal error in a single cell’s classification can produce strange results. • % < Min: The current percentage of cells below the minimum elevation specified.	Greenhouse gas mass sequestered (CO2) ? Comment: Product of the Carbon Sequestration module. SLAMM estimates Carbon Sequestration as a function of land cover based on the approach developed by Vandebroek and Crooks at ESA PWA (2014). This method accounts for both the amount of Carbon sequestered by wetlands as well as the Carbon emissions through the loss of methane from freshwater habitats. Carbon sequestration calculations will be performed for all time-steps and output steps for all simulations performed and all modeled subsites.	Infrastructure inundation frequency ? Comment: At the end of a SLAMM the frequency that each infrastructure point will be inundated for <30, 30-60, 60-90 days under normal tides and storm-surge conditions are summarized in the output excel file.	Probability of having submerged aquatic vegetation ? Comment: Product of the optional Submerged Aquatic Vegetation module. SLAMM uses a regression relationship developed by Melanie Frazier and Patrick Clinton of U.S. EPA to describe the probability of submerged aquatic vegetation being present in a given cell. The default parameters as delivered with SLAMM 6.7 were derived using data from the Yaquina estuary in Oregon and the relationship was then validated at the Tilamook and Alsea estuaries in Oregon. When this model is implemented, probability-of-SAV maps may be produced by the model in each time step.	Road miles inundated ? Comment: At the end of a SLAMM simulations numerical data of the total length of roads that are inundated <30, 30-60, 60-90 days are summarized in the output excel file.	Road segment inundation (30, 60, and 90 day frequency) ? Comment: At the end of a SLAMM the frequency that each infrastructure point will be inundated for <30, 30-60, 60-90 days under normal tides and storm-surge conditions are summarized in the output excel file.	Total area of submerged aquatic vegetation ? Comment: Product of the optional Submerged Aquatic Vegetation module. The expected value of total SAV habitat in square kilometers is output along with other SLAMM tables of output. The default parameters as delivered with SLAMM 6.7 were derived using data from the Yaquina estuary in Oregon and the relationship was then validated at the Tilamook and Alsea estuaries in Oregon.
Variable ID variable.detail.varIdHelp ?	20443	20440	20434	20441	20433	21925	20442
Symbol variable.detail.varSymbolHelp ?	Not reported	M sub	Not reported	PROBSAV	Not reported	Not reported	Not reported
Qualitative-Quantitative variable.detail.continuousCategoricalHelp ?	Qualitative (Class, Rating or Ranking)	Quantitative (Cardinal Only)	Quantitative (Cardinal Only)	Quantitative (Cardinal Only)	Quantitative (Cardinal Only)	Quantitative (Cardinal Only)	Quantitative (Cardinal Only)
Cardinal-Ordinal variable.detail.cardinalOrdinalHelp ?	Non-Ordinal	Cardinal	Cardinal	Cardinal	Cardinal	Cardinal	Cardinal
Units variable.detail.varUnitsHelp ?	Not applicable	metric tons ha^-1 yr^-1	days	%	mi	days	km^2

Variable Typology

Name variable.detail.varNameHelp ?	Change in wetland type ? Comment: Map distributions of wetlands are predicted under conditions of accelerated sea level rise, and results are summarized in tabular and graphical form. For each time step the fractional conversion from one class to another is computed on the basis of the relative change in elevation divided by the elevation range of the class in that cell. In addition to mapped output: Available Statistics include: • n cells: The number of cells covered by that land category. Statistics based on small sample sizes should probably be discounted to some degree. • 5th percentile and 95th percentile: The 90% confidence interval for this particular land category in half-tide units. These can be compared with the “Min HTU” and “Max HTU” conceptual model columns. • Mean, St. Dev.: The average elevation value and standard deviation in half tide units. • Min, Max: The minimum and maximum elevation for this cell in half-tide units. These data are usually less useful as horizontal error in a single cell’s classification can produce strange results. • % < Min: The current percentage of cells below the minimum elevation specified.	Greenhouse gas mass sequestered (CO2) ? Comment: Product of the Carbon Sequestration module. SLAMM estimates Carbon Sequestration as a function of land cover based on the approach developed by Vandebroek and Crooks at ESA PWA (2014). This method accounts for both the amount of Carbon sequestered by wetlands as well as the Carbon emissions through the loss of methane from freshwater habitats. Carbon sequestration calculations will be performed for all time-steps and output steps for all simulations performed and all modeled subsites.	Infrastructure inundation frequency ? Comment: At the end of a SLAMM the frequency that each infrastructure point will be inundated for <30, 30-60, 60-90 days under normal tides and storm-surge conditions are summarized in the output excel file.	Probability of having submerged aquatic vegetation ? Comment: Product of the optional Submerged Aquatic Vegetation module. SLAMM uses a regression relationship developed by Melanie Frazier and Patrick Clinton of U.S. EPA to describe the probability of submerged aquatic vegetation being present in a given cell. The default parameters as delivered with SLAMM 6.7 were derived using data from the Yaquina estuary in Oregon and the relationship was then validated at the Tilamook and Alsea estuaries in Oregon. When this model is implemented, probability-of-SAV maps may be produced by the model in each time step.	Road miles inundated ? Comment: At the end of a SLAMM simulations numerical data of the total length of roads that are inundated <30, 30-60, 60-90 days are summarized in the output excel file.	Road segment inundation (30, 60, and 90 day frequency) ? Comment: At the end of a SLAMM the frequency that each infrastructure point will be inundated for <30, 30-60, 60-90 days under normal tides and storm-surge conditions are summarized in the output excel file.	Total area of submerged aquatic vegetation ? Comment: Product of the optional Submerged Aquatic Vegetation module. The expected value of total SAV habitat in square kilometers is output along with other SLAMM tables of output. The default parameters as delivered with SLAMM 6.7 were derived using data from the Yaquina estuary in Oregon and the relationship was then validated at the Tilamook and Alsea estuaries in Oregon.
Predictor-Intermediate-Response variable.detail.displayVariableTypeHelp ?	Response	Response	Response	Response	Response	Response	Response
Predictor Variable Type variable.detail.displayPredictorVariableTypeHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Response Variable Type variable.detail.resClassHelp ?	Computed Variable	Computed Variable	Computed Variable	Computed Variable	Computed Variable	Computed Variable	Computed Variable
Data Source/Type variable.detail.dataTypeHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Variable Classification Hierarchy variable.detail.vchLevel1Help ?	5. Ecosystem Attributes and Potential Supply of Ecosystem Goods and Services	5. Ecosystem Attributes and Potential Supply of Ecosystem Goods and Services	6. Non-monetary Indicators of Human Demand, Use or Benefit of Ecosystem Goods and Services	5. Ecosystem Attributes and Potential Supply of Ecosystem Goods and Services	6. Non-monetary Indicators of Human Demand, Use or Benefit of Ecosystem Goods and Services	6. Non-monetary Indicators of Human Demand, Use or Benefit of Ecosystem Goods and Services	5. Ecosystem Attributes and Potential Supply of Ecosystem Goods and Services
	--Biological characteristics, processes or requirements of living ecosystem components	--CICES categories: Ecosystem goods and services - or landscape-level indices of suitability to supply EGS	--Demand for or use of regulation & maintenance services-Mediation of flows	--Biological characteristics, processes or requirements of living ecosystem components	--Demand for or use of regulation & maintenance services-Mediation of flows	--Demand for or use of regulation & maintenance services-Mediation of flows	--Biological characteristics, processes or requirements of living ecosystem components
	----Biological characteristics, processes or requirements of ecological communities	----Suitability to supply regulation & maintenance services-Mediation of wastes	----Flood and storm protection	----Biological characteristics, processes or requirements of ecological communities	----Flood and storm protection	----Flood and storm protection	----Biological characteristics, processes or requirements of ecological communities
	------Near coastal marine, estuarine, and coral communities	------Filtration/sequestration/storage/accumulation by ecosystems		------Near coastal marine, estuarine, and coral communities			------Near coastal marine, estuarine, and coral communities

Variable Spatial Characteristics

Name variable.detail.varNameHelp ?	Change in wetland type ? Comment: Map distributions of wetlands are predicted under conditions of accelerated sea level rise, and results are summarized in tabular and graphical form. For each time step the fractional conversion from one class to another is computed on the basis of the relative change in elevation divided by the elevation range of the class in that cell. In addition to mapped output: Available Statistics include: • n cells: The number of cells covered by that land category. Statistics based on small sample sizes should probably be discounted to some degree. • 5th percentile and 95th percentile: The 90% confidence interval for this particular land category in half-tide units. These can be compared with the “Min HTU” and “Max HTU” conceptual model columns. • Mean, St. Dev.: The average elevation value and standard deviation in half tide units. • Min, Max: The minimum and maximum elevation for this cell in half-tide units. These data are usually less useful as horizontal error in a single cell’s classification can produce strange results. • % < Min: The current percentage of cells below the minimum elevation specified.	Greenhouse gas mass sequestered (CO2) ? Comment: Product of the Carbon Sequestration module. SLAMM estimates Carbon Sequestration as a function of land cover based on the approach developed by Vandebroek and Crooks at ESA PWA (2014). This method accounts for both the amount of Carbon sequestered by wetlands as well as the Carbon emissions through the loss of methane from freshwater habitats. Carbon sequestration calculations will be performed for all time-steps and output steps for all simulations performed and all modeled subsites.	Infrastructure inundation frequency ? Comment: At the end of a SLAMM the frequency that each infrastructure point will be inundated for <30, 30-60, 60-90 days under normal tides and storm-surge conditions are summarized in the output excel file.	Probability of having submerged aquatic vegetation ? Comment: Product of the optional Submerged Aquatic Vegetation module. SLAMM uses a regression relationship developed by Melanie Frazier and Patrick Clinton of U.S. EPA to describe the probability of submerged aquatic vegetation being present in a given cell. The default parameters as delivered with SLAMM 6.7 were derived using data from the Yaquina estuary in Oregon and the relationship was then validated at the Tilamook and Alsea estuaries in Oregon. When this model is implemented, probability-of-SAV maps may be produced by the model in each time step.	Road miles inundated ? Comment: At the end of a SLAMM simulations numerical data of the total length of roads that are inundated <30, 30-60, 60-90 days are summarized in the output excel file.	Road segment inundation (30, 60, and 90 day frequency) ? Comment: At the end of a SLAMM the frequency that each infrastructure point will be inundated for <30, 30-60, 60-90 days under normal tides and storm-surge conditions are summarized in the output excel file.	Total area of submerged aquatic vegetation ? Comment: Product of the optional Submerged Aquatic Vegetation module. The expected value of total SAV habitat in square kilometers is output along with other SLAMM tables of output. The default parameters as delivered with SLAMM 6.7 were derived using data from the Yaquina estuary in Oregon and the relationship was then validated at the Tilamook and Alsea estuaries in Oregon.
Spatial Extent Area variable.detail.spExtentHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Spatially Distributed? variable.detail.spDistributedHelp ?	Yes	Yes	Yes	Yes	Yes	Yes	No
Observations Spatially Patterned? variable.detail.regularSpGrainHelp ?	Yes	Yes	Yes	Yes	Yes	Yes	Not applicable
Spatial Grain Type variable.detail.spGrainTypeHelp ?	area, for pixel or radial feature	area, for pixel or radial feature	area, for pixel or radial feature	area, for pixel or radial feature	area, for pixel or radial feature	area, for pixel or radial feature	Not applicable
Spatial Grain Size variable.detail.spGrainSizeHelp ?	user defined	user defined	user defined	user defined	user defined	user defined	Not applicable
Spatial Density variable.detail.spDensityHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
EnviroAtlas URL variable.detail.enviroAtlasURLHelp ?

Variable Temporal Characteristics

Name variable.detail.varNameHelp ?	Change in wetland type ? Comment: Map distributions of wetlands are predicted under conditions of accelerated sea level rise, and results are summarized in tabular and graphical form. For each time step the fractional conversion from one class to another is computed on the basis of the relative change in elevation divided by the elevation range of the class in that cell. In addition to mapped output: Available Statistics include: • n cells: The number of cells covered by that land category. Statistics based on small sample sizes should probably be discounted to some degree. • 5th percentile and 95th percentile: The 90% confidence interval for this particular land category in half-tide units. These can be compared with the “Min HTU” and “Max HTU” conceptual model columns. • Mean, St. Dev.: The average elevation value and standard deviation in half tide units. • Min, Max: The minimum and maximum elevation for this cell in half-tide units. These data are usually less useful as horizontal error in a single cell’s classification can produce strange results. • % < Min: The current percentage of cells below the minimum elevation specified.	Greenhouse gas mass sequestered (CO2) ? Comment: Product of the Carbon Sequestration module. SLAMM estimates Carbon Sequestration as a function of land cover based on the approach developed by Vandebroek and Crooks at ESA PWA (2014). This method accounts for both the amount of Carbon sequestered by wetlands as well as the Carbon emissions through the loss of methane from freshwater habitats. Carbon sequestration calculations will be performed for all time-steps and output steps for all simulations performed and all modeled subsites.	Infrastructure inundation frequency ? Comment: At the end of a SLAMM the frequency that each infrastructure point will be inundated for <30, 30-60, 60-90 days under normal tides and storm-surge conditions are summarized in the output excel file.	Probability of having submerged aquatic vegetation ? Comment: Product of the optional Submerged Aquatic Vegetation module. SLAMM uses a regression relationship developed by Melanie Frazier and Patrick Clinton of U.S. EPA to describe the probability of submerged aquatic vegetation being present in a given cell. The default parameters as delivered with SLAMM 6.7 were derived using data from the Yaquina estuary in Oregon and the relationship was then validated at the Tilamook and Alsea estuaries in Oregon. When this model is implemented, probability-of-SAV maps may be produced by the model in each time step.	Road miles inundated ? Comment: At the end of a SLAMM simulations numerical data of the total length of roads that are inundated <30, 30-60, 60-90 days are summarized in the output excel file.	Road segment inundation (30, 60, and 90 day frequency) ? Comment: At the end of a SLAMM the frequency that each infrastructure point will be inundated for <30, 30-60, 60-90 days under normal tides and storm-surge conditions are summarized in the output excel file.	Total area of submerged aquatic vegetation ? Comment: Product of the optional Submerged Aquatic Vegetation module. The expected value of total SAV habitat in square kilometers is output along with other SLAMM tables of output. The default parameters as delivered with SLAMM 6.7 were derived using data from the Yaquina estuary in Oregon and the relationship was then validated at the Tilamook and Alsea estuaries in Oregon.
Temporal Extent variable.detail.tempExtentHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Temporally Distributed? variable.detail.tempDistributedHelp ?	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Regular Temporal Grain? variable.detail.regularTempGrainHelp ?	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Temporal Grain Size Value variable.detail.tempGrainSizeValHelp ?	user defined	user defined	user defined	user defined	user defined	user defined	user defined
Temporal Grain Size Units variable.detail.tempGrainSizeUnitHelp ?	Year	Year	Year	Year	Year	Year	Year
Temporal Density variable.detail.tempDensityHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable

Variable Values

Name variable.detail.varNameHelp ?	Change in wetland type ? Comment: Map distributions of wetlands are predicted under conditions of accelerated sea level rise, and results are summarized in tabular and graphical form. For each time step the fractional conversion from one class to another is computed on the basis of the relative change in elevation divided by the elevation range of the class in that cell. In addition to mapped output: Available Statistics include: • n cells: The number of cells covered by that land category. Statistics based on small sample sizes should probably be discounted to some degree. • 5th percentile and 95th percentile: The 90% confidence interval for this particular land category in half-tide units. These can be compared with the “Min HTU” and “Max HTU” conceptual model columns. • Mean, St. Dev.: The average elevation value and standard deviation in half tide units. • Min, Max: The minimum and maximum elevation for this cell in half-tide units. These data are usually less useful as horizontal error in a single cell’s classification can produce strange results. • % < Min: The current percentage of cells below the minimum elevation specified.	Greenhouse gas mass sequestered (CO2) ? Comment: Product of the Carbon Sequestration module. SLAMM estimates Carbon Sequestration as a function of land cover based on the approach developed by Vandebroek and Crooks at ESA PWA (2014). This method accounts for both the amount of Carbon sequestered by wetlands as well as the Carbon emissions through the loss of methane from freshwater habitats. Carbon sequestration calculations will be performed for all time-steps and output steps for all simulations performed and all modeled subsites.	Infrastructure inundation frequency ? Comment: At the end of a SLAMM the frequency that each infrastructure point will be inundated for <30, 30-60, 60-90 days under normal tides and storm-surge conditions are summarized in the output excel file.	Probability of having submerged aquatic vegetation ? Comment: Product of the optional Submerged Aquatic Vegetation module. SLAMM uses a regression relationship developed by Melanie Frazier and Patrick Clinton of U.S. EPA to describe the probability of submerged aquatic vegetation being present in a given cell. The default parameters as delivered with SLAMM 6.7 were derived using data from the Yaquina estuary in Oregon and the relationship was then validated at the Tilamook and Alsea estuaries in Oregon. When this model is implemented, probability-of-SAV maps may be produced by the model in each time step.	Road miles inundated ? Comment: At the end of a SLAMM simulations numerical data of the total length of roads that are inundated <30, 30-60, 60-90 days are summarized in the output excel file.	Road segment inundation (30, 60, and 90 day frequency) ? Comment: At the end of a SLAMM the frequency that each infrastructure point will be inundated for <30, 30-60, 60-90 days under normal tides and storm-surge conditions are summarized in the output excel file.	Total area of submerged aquatic vegetation ? Comment: Product of the optional Submerged Aquatic Vegetation module. The expected value of total SAV habitat in square kilometers is output along with other SLAMM tables of output. The default parameters as delivered with SLAMM 6.7 were derived using data from the Yaquina estuary in Oregon and the relationship was then validated at the Tilamook and Alsea estuaries in Oregon.
Units variable.detail.estUnitHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Min Value variable.detail.minEstHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Max Value variable.detail.estHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Other Value Type variable.detail.natureOtherEstHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Other Value variable.detail.otherEstHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable

Variable Variability and Sensitivity

Name variable.detail.varNameHelp ?	Change in wetland type ? Comment: Map distributions of wetlands are predicted under conditions of accelerated sea level rise, and results are summarized in tabular and graphical form. For each time step the fractional conversion from one class to another is computed on the basis of the relative change in elevation divided by the elevation range of the class in that cell. In addition to mapped output: Available Statistics include: • n cells: The number of cells covered by that land category. Statistics based on small sample sizes should probably be discounted to some degree. • 5th percentile and 95th percentile: The 90% confidence interval for this particular land category in half-tide units. These can be compared with the “Min HTU” and “Max HTU” conceptual model columns. • Mean, St. Dev.: The average elevation value and standard deviation in half tide units. • Min, Max: The minimum and maximum elevation for this cell in half-tide units. These data are usually less useful as horizontal error in a single cell’s classification can produce strange results. • % < Min: The current percentage of cells below the minimum elevation specified.	Greenhouse gas mass sequestered (CO2) ? Comment: Product of the Carbon Sequestration module. SLAMM estimates Carbon Sequestration as a function of land cover based on the approach developed by Vandebroek and Crooks at ESA PWA (2014). This method accounts for both the amount of Carbon sequestered by wetlands as well as the Carbon emissions through the loss of methane from freshwater habitats. Carbon sequestration calculations will be performed for all time-steps and output steps for all simulations performed and all modeled subsites.	Infrastructure inundation frequency ? Comment: At the end of a SLAMM the frequency that each infrastructure point will be inundated for <30, 30-60, 60-90 days under normal tides and storm-surge conditions are summarized in the output excel file.	Probability of having submerged aquatic vegetation ? Comment: Product of the optional Submerged Aquatic Vegetation module. SLAMM uses a regression relationship developed by Melanie Frazier and Patrick Clinton of U.S. EPA to describe the probability of submerged aquatic vegetation being present in a given cell. The default parameters as delivered with SLAMM 6.7 were derived using data from the Yaquina estuary in Oregon and the relationship was then validated at the Tilamook and Alsea estuaries in Oregon. When this model is implemented, probability-of-SAV maps may be produced by the model in each time step.	Road miles inundated ? Comment: At the end of a SLAMM simulations numerical data of the total length of roads that are inundated <30, 30-60, 60-90 days are summarized in the output excel file.	Road segment inundation (30, 60, and 90 day frequency) ? Comment: At the end of a SLAMM the frequency that each infrastructure point will be inundated for <30, 30-60, 60-90 days under normal tides and storm-surge conditions are summarized in the output excel file.	Total area of submerged aquatic vegetation ? Comment: Product of the optional Submerged Aquatic Vegetation module. The expected value of total SAV habitat in square kilometers is output along with other SLAMM tables of output. The default parameters as delivered with SLAMM 6.7 were derived using data from the Yaquina estuary in Oregon and the relationship was then validated at the Tilamook and Alsea estuaries in Oregon.
Variability Expression Given? variable.detail.variabilityExpHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Variability Metric variable.detail.variabilityMetricHelp ?	None	None	None	None	None	None	None
Variability Value variable.detail.variabilityValueHelp ?	None	None	None	None	None	None	None
Variability Units	None	None	None	None	None	None	None
Resampling Used? variable.detail.bootstrappingHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Variability Expression Used in Modeling? variable.detail.variabilityUsedHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable

Variable Operational Validation (Response Variables only)

Name variable.detail.varNameHelp ?	Change in wetland type	Greenhouse gas mass sequestered (CO2)	Infrastructure inundation frequency	Probability of having submerged aquatic vegetation	Road miles inundated	Road segment inundation (30, 60, and 90 day frequency)	Total area of submerged aquatic vegetation
Variable ID variable.detail.varIdHelp ?	20443	20440	20434	20441	20433	21925	20442
Validated? variable.detail.resValidatedHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Validation Approach (within, between, etc.) variable.detail.validationApproachHelp ?	None	None	None	None	None	None	None
Validation Quality (Qual/Quant) variable.detail.validationQualityHelp ?	None	None	None	None	None	None	None
Validation Method (Stat/Deviance) variable.detail.validationMethodHelp ?	None	None	None	None	None	None	None
Validation Metric variable.detail.validationMetricHelp ?	None	None	None	None	None	None	None
Validation Value variable.detail.validationValHelp ?	None	None	None	None	None	None	None
Validation Units	None	None	None	None	None	None	None
Use of Measured Response Data variable.detail.measuredResponseDataHelp ?	None	None	None	None	None	None	None