Type and Unit definitions
Adjustment factor distribution method types
Accepted justment factor distribution method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
No adjustment factor |
None |
No adjustment factor. |
|
Fixed adjustment factor |
Fixed |
Fixed adjustment factor. |
|
LogNormal |
LogNormal |
Lognormal distribution with parameters a and b and offset c (default c = 0). |
|
LogStudents_t |
LogStudents_t |
Log Students-t distribution with parameters a, b and c and offset d (default d = 0). |
|
Beta |
Beta |
Beta distribution with shape parameters a and b on interval [c, d], (default = 0, 1). |
|
Gamma |
Gamma |
Gamma distribution with shape parameter a and rate parameter b with offset = c (default = 0). |
Assessment group membership calculation methods
Accepted Assessment group membership calculation methods. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Any (crisp) |
Any (crisp) |
Assign the highest membership value as membership. For crisp memberships, assign positive substance membership if any model indicates positive membership, and negative membership otherwise. |
|
Majority (crisp) |
Majority (crisp) |
Assign positive substance membership if the majority of the membership models indicates positive membership, otherwise, the substance is considered not to be in the assessment group. |
|
Ratio (probabilistic) |
Ratio (probabilistic) |
Express substance membership as a probability ranging from zero (certainly out) to one (certainly in), computed as the average membership score. |
|
Bayesian (probabilistic) |
Bayesian (probabilistic) |
Express substance memberships as a probability with values ranging from zero (certainly out) to one (certainly in) computed using a Bayesian approach. |
Benchmark response type
Accepted benchmark response types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Fraction change |
Fraction change |
FractionChange, FactorChange |
The benchmark response is defined as a fraction change of the background response (i.e., defined for both increase and decrease). E.g., for a factor of 0.1, the benchmark response is at +/- 10% of background response. |
Percentage change |
Percentage change |
PercentageChange |
The benchmark response is defined as a percentage change of the background response (i.e., defined for both increase and decrease). E.g., for a percentage of 10, the benchmark response is at +/- 10% of background response. |
Fraction of background response |
Fraction of background |
Factor, FactorOfBackground |
The benchmark response is defined as a fraction of the background response. E.g., for a factor of 0.9, the benchmark response is at 0.9 times the background response (i.e., a decrease). |
Percentage of background response |
Percentage of background |
Percentage, PercentageOfBackground |
The benchmark response is defined as a percentage of the background response. E.g., for a percentage of 90, the benchmark response is at 90% of the background response (i.e., a decrease). |
Extra risk |
ER |
ExtraRisk |
For quantal response types. The benchmark dose is defined as the dose that corresponding with an extra risk of a factor times the background risk. A factor of 0.05 corresponds with 5% extra risk. |
Additional risk |
AR |
AdditionalRisk |
For quantal response types. The benchmark dose is defined as the dose that corresponding with an additional risk of a factor times the background risk. A factor of 0.05 corresponds with 5% additional risk. |
ED50 |
ED50 |
ED50 |
For quantal response types. The benchmark dose is defined as the dose that corresponds with an estimated risk of 50% (ED50). |
Absolute threshold value |
Threshold value |
Absolute |
The benchmark dose is defined as an absolute threshold value. |
Absolute difference |
Absolute difference |
Difference |
The benchmark dose is defined an absolute difference with the background risk. |
Biological organisation type
Accepted biological organisation types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Molecular |
Molecular |
Molecular |
Molecular level |
Cellular |
Cellular |
Cellular |
Cellular level |
Tissue |
Tissue |
Tissue |
Tissue level |
Organ |
Organ |
Organelle, Organ |
Organ level |
Individual |
Individual |
Individual |
Whole body level |
Population |
Population |
Population |
Population level |
Body weight unit
Accepted units for person body weights. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
Kilogram |
kg |
kg, kilograms, kilogr, 3, G167A |
Gram |
g |
g, grams, gr, 0, G148A |
Boolean type
Accepted boolean types. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
True |
True |
True, Yes, T, Y |
False |
False |
False, F, No, N |
Cluster method type
Accepted cluster method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Component selection (SNMU) |
NoClustering |
Only component selection is performed. |
|
Component selection and population subgrouping (SNMU + k-means clustering) |
Kmeans |
Component selection followed by K-Means clustering of individuals based on their component exposure. K-means classifies individuals in multiple groups (i.e., clusters), such that individuals within the same cluster are as similar as possible (i.e., high intra-class similarity), whereas individuals from different clusters are as dissimilar as possible (i.e., low inter-class similarity). In k-means clustering, each cluster is represented by its center (i.e, centroid) which corresponds to the mean of points assigned to the cluster. |
|
Component selection and population subgrouping (SNMU + hierarchical clustering) |
Hierarchical |
Component selection followed by hierarchical (Ward’s) clustering of individuals based on their component exposure. Hierachical clustering builds a hierarchy from the bottom-up, and doesn’t require to specify the number of clusters beforehand. Hierarchical clustering produces a tree-based representation of the observations known as a dendrogram. |
Combination method membership info and PoD presence types
Accepted Combination method membership info and PoD presence types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Consider active if POD/HC AND (in-silico) memberships indicate active |
Intersection |
Consider active if POD/HC AND (in-silico) memberships indicate active. |
|
Consider active if POD/HC OR (in-silico) memberships indicates active |
Union |
Consider active if POD/HC OR (in-silico) memberships indicates active. |
Concentration limit value type
Accepted concentration limit value types. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
Maximum residue limit |
MRL |
MRL, MaximumResidueLimit |
Proposed maximum residue limit |
Proposed-MRL |
ProposedMrl, ProposedMaximumResidueLimit |
Concentration model choice types
Accepted Concentration model choice types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Custom |
Custom |
By setting this tier to custom, the exposure model can be configured in any way desirable (without tier specific presets). The model is fully specified by the user. Both EFSA 2012 Optimistic and EFSA 2012 Pessimistic can be specified using the custom model choice. This choice allows for a sensitivity analysis where each factor is varied, one at the time. |
|
EFSA 2012 Optimistic |
EfsaOptimistic |
EFSA 2012 Optimistic. |
|
EFSA 2012 Pessimistic |
EfsaPessimistic |
EFSA 2012 Pessimistic. |
|
EC 2018 Tier 1 |
ComTier1 |
EC 2018 Tier 1. |
|
EC 2018 Tier 2 |
ComTier2 |
EC 2018 Tier 2. |
|
EFSA 2012 Pessimistic - Acute |
EfsaPessimisticAcute |
EFSA 2012 Pessimistic - Acute. |
|
EFSA 2012 Pessimistic - Chronic |
EfsaPessimisticChronic |
EFSA 2012 Pessimistic - Chronic. |
Concentration model types
Accepted Concentration model types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Empirical |
Empirical |
Residues are sampled from the empirical distribution. Fallback: zero. |
|
Censored value Spike LogNormal |
CVSpike-LogN |
A lognormal model (logarithmic transformed values, with parameters mu and sigma^2) is fitted to the positive residues values. LOR information is not used. Fallback (if number of positives less than 2): Empirical, but Maximum Residu Limit for pessimistic assessments. |
|
Censored Spike Truncated LogNormal |
CVSpike-TruncLogN |
A truncated lognormal model (with parameters mu and sigma^2) is fitted to the positive residues values. The LOR is used to estimate the truncated left tail of the distribution. Fallback: Lognormal non-detect spike. |
|
Censored LogNormal |
CensLogN |
Advanced. A censored lognormal model (with parameters mu and sigma^2) is fitted to the censored and positives residue values. Note, this model is not available when agricultural use information is used. Fallback: Lognormal non-detect spike. |
|
Zero Spike Censored LogNormal |
ZeroSpike-CensLogN |
Advanced. A mixture model with zero spike (p0) and censored lognormal model (with parameters mu and sigma^2) is fitted to the censored and positives residue values. Note, this model is not available when agricultural use information is used. Fallback: Censored lognormal. |
|
Censored Spike Maximum Residue Limit |
CVSpike-MRL |
Censored Spike Maximum Residue Limit. |
|
Summary statistics |
Summary statistic |
Summary statistics. |
|
LogNormal |
LogN |
Lognormal model. |
Concentration unit
Accepted units for substance concentrations. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
kilogram/kilogram |
kg/kg |
kg/kg, kilogram/kilogram, kilogram/kg, 0, G063A |
gram/kilogram |
g/kg |
g/kg, gram/kilogram, gram/kg, gr/kg, -3, G015A, G060A, G191A |
milligram/kilogram |
mg/kg |
mg/kg, milligram/kilogram, milligram/kg, milligr/kg, -6, G049A, G061A |
microgram/kilogram |
µg/kg |
µg/kg, ug/kg, microgram/kilogram, microgram/kg, microgr/kg, -9, G050A, G076A |
nanogram/kilogram |
ng/kg |
ng/kg, nanogram/kilogram, nanogram/kg, nanogr/kg, -12, G077A, G080A |
picogram/kilogram |
pg/kg |
pg/kg, picogram/kilogram, picogram/kg, picogr/kg, -15, G081A |
kilogram/liter |
kg/L |
kg/l, kg/L, kilogram/liter, kilogram/litre, G017A |
gram/liter |
g/L |
g/l, g/L, gram/liter, gram/litre, gr/l, gr/L, G016A |
milligram/liter |
mg/L |
mg/l, mg/L, milligram/liter, milligram/litre, milligr/l, milligr/L, G052A, G062A |
microgram/liter |
µg/L |
µg/l, ug/L, microgram/liter, microgram/litre, microgr/l, microgr/L, G051A, G079A |
nanogram/liter |
ng/L |
ng/l, ng/L, nanogram/liter, nanogram/litre, nanogr/l, nanogr/L, G078A |
picogram/liter |
pg/L |
pg/l, pg/L, picogram/liter, picogram/litre, picogr/l, picogr/L |
microgram/milliliter |
µg/mL |
µg/ml, ug/mL, microgram/milliliter, microgram/millilitre, microgr/ml, microgr/mL |
nanogram/milliliter |
ng/mL |
ng/ml, ng/mL, nanogram/milliliter, nanogram/millilitre, nanogr/ml, nanogr/mL |
Concentration value type
Accepted concentration value type. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Mean concentration |
MC |
MeanConcentration, ConcentrationMean, MC |
Mean value from the residue trials. |
Median concentration |
MR |
MedianConcentration, MR, STMR, SupervisedTrialMedianResidue |
Median concentration / residue value of the positive measurements of the residue trials. |
Highest concentration |
HR |
HighestConcentration, HighestResidue, HR |
Highest measured residue / concentration value. |
Concentration percentile |
CP |
Percentile |
|
Limit of quantification |
LOQ |
LOQ |
|
Maximum residue limit |
MRL |
MRL |
Concentrations tier types
Accepted Concentrations tier types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Custom |
Custom |
By setting this tier to custom, the exposure model can be configured in any way desirable (without tier specific presets). The model is fully specified by the user. Both EFSA 2012 Optimistic and EFSA 2012 Pessimistic can be specified using the custom model choice. This choice allows for a sensitivity analysis where each factor is varied, one at the time. |
|
EC 2018 Tier 1 |
ComTier1 |
EC 2018 Tier 1. |
|
EC 2018 Tier 2 |
ComTier2 |
EC 2018 Tier 2. |
Consumption intake unit
Accepted units for consumption intake amounts. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
gram/kilogram bodyweight/day |
g/kg bw/day |
g/kg bw, gram/kg bw, g/kg bw/day, gram/kg bw/day, gr/kg bw/day, G212A |
gram/day |
g/day |
gram, grams, g/day, g/day, gram/day, gr/day |
Consumption unit
Accepted units for consumption amounts. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
kilogram |
kg |
kg, kilograms, kilogr, 3, G167A |
Gram |
g |
g, grams, gr, 0, G148A |
Consumption value type
Accepted consumption value types. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
Large portion |
LP |
LP, LargePortion |
Mean consumption |
MC |
MC, MeanConsumption |
Percentile |
Percentile |
Percentile, P |
Covariate model types
Accepted Covariate model types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Only constant |
Constant |
No relation between exposure and e.g. age or gender. |
|
Only covariable |
Covariable |
Exposure depends on the covariable, e.g. age. |
|
Only cofactor |
Cofactor |
Exposure depends on the level of the cofactor, e.g. gender. |
|
Both covariable and cofactor |
CovariableCofactor |
Exposure depends on both covariable and cofactor (additive model). |
|
Both covariable and cofactor and interaction |
CovariableCofactorInteraction |
Exposure depends on both covariable and cofactor and the effect of the covariable differs for different levels of the cofactor (multiplicative model). |
Dietary exposures details level types
Accepted ietary exposures details level types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Full |
Full |
Show all details. |
|
Restrict to risk-drivers (dietary exposures screening) |
OnlyRiskDrivers |
Restrict to detailed output for risk-drivers identified by dietary exposures screening. |
|
Omit foods-as-eaten details |
OmitFoodsAsEaten |
Restrict to detailed output for modelled foods and substances. Omit foods-as-eaten details. |
Dietary intake calculation tier types
Accepted Dietary intake calculation tier types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Custom |
Custom |
By setting this tier to custom, the exposure model can be configured in any way desirable (without tier specific presets). |
|
EFSA 2012 Optimistic |
EfsaOptimistic |
EFSA 2012 Optimistic. |
|
EFSA 2012 Pessimistic |
EfsaPessimistic |
EFSA 2012 Pessimistic. |
|
EC 2018 Tier 1 |
ComTier1 |
EC 2018 Tier 1. |
|
EC 2018 Tier 2 |
ComTier2 |
EC 2018 Tier 2. |
|
EFSA 2012 Pessimistic - Acute |
EfsaPessimisticAcute |
EFSA 2012 Pessimistic - Acute. |
|
EFSA 2012 Pessimistic - Chronic |
EfsaPessimisticChronic |
EFSA 2012 Pessimistic - Chronic. |
Dose response model type
Accepted dose response model types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Exp-m1 |
Exp-m1 |
Expm1 |
Exponential model 1 |
Exp-m2 |
Exp-m2 |
Expm2 |
Exponential model 2 |
Exp-m3 |
Exp-m3 |
Expm3 |
Exponential model 3 |
Exp-m4 |
Exp-m4 |
Expm4 |
Exponential model 4 |
Exp-m5 |
Exp-m5 |
Expm5 |
Exponential model 5 |
Hill-m1 |
Hill-m1 |
Hillm1 |
Hill model 1 |
Hill-m2 |
Hill-m2 |
Hillm2 |
Hill model 2 |
Hill-m3 |
Hill-m3 |
Hillm3 |
Hill model 3 |
Hill-m4 |
Hill-m4 |
Hillm4 |
Hill model 4 |
Hill-m5 |
Hill-m5 |
Hillm5 |
Hill model 5 |
TwoStage |
TwoStage |
TwoStage |
|
LogLogist |
LogLogist |
LogLogist |
|
Weibull |
Weibull |
Weibull |
|
LogProb |
LogProb |
LogProb |
|
Gamma |
Gamma |
Gamma |
|
Logistic |
Logistic |
Logistic |
|
Probit |
Probit |
Probit |
|
LVM Exp m2 |
LVM Exp m2 |
LVM Exp m2 |
|
LVM Exp m3 |
LVM Exp m3 |
LVM_Exp_M3 |
|
LVM Exp m4 |
LVM Exp m4 |
LVM_Exp_M4 |
|
LVM Exp m5 |
LVM Exp m5 |
LVM_Exp_M5 |
|
LVM Hill m2 |
LVM Hill m2 |
LVM Hill m2 |
|
LVM Hill m3 |
LVM Hill m3 |
LVM_Hill_M3 |
|
LVM Hill m4 |
LVM Hill m4 |
LVM_Hill_M4 |
|
LVM Hill m5 |
LVM Hill m5 |
LVM Hill m5 |
Dose unit
Accepted units for substance doses. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
gram/kilogram bodyweight/day |
g/kg bw/day |
g/kg bw/day, gram/kg bw/day, gr/kg bw/day, G212A |
milligram/kilogram bodyweight/day |
mg/kg bw/day |
mg/kg bw/day, milligram/kg bw/day, milligr/kg bw/day, G211A |
microgram/kilogram bodyweight/day |
µg/kg bw/day |
µg/kg bw/day, microgram/kg bw/day, microgr/kg bw/day, G210A |
nanogram/kilogram bodyweight/day |
ng/kg bw/day |
ng/kg bw/day, nanogram/kg bw/day, nanogr/kg bw/day, G214A |
picogram/kilogram bodyweight/day |
pg/kg bw/day |
pg/kg bw/day, picogram/kg bw/day, picogr/kg bw/day |
femtogram/kilogram bodyweight/day |
fg/kg bw/day |
fg/kg bw/day, femtogram/kg bw/day, femtogr/kg bw/day |
gram/gram bodyweight/day |
g/g bw/day |
g/g bw/day, gram/g bw/day, gr/g bw/day |
milligram/gram bodyweight/day |
mg/g bw/day |
mg/g bw/day, milligram/g bw/day, milligr/g bw/day |
microgram/gram bodyweight/day |
µg/g bw/day |
µg/g bw/day, microgram/g bw/day, microgr/g bw/day |
nanogram/gram bodyweight/day |
ng/g bw/day |
ng/g bw/day, nanogram/g bw/day, nanogr/g bw/day |
picogram/gram bodyweight/day |
pg/g bw/day |
pg/g bw/day, picogram/g bw/day, picogr/g bw/day |
femtogram/gram bodyweight/day |
fg/g bw/day |
fg/g bw/day, femtogram/g bw/day, femtogr/g bw/day |
kilogram/day |
kg/day |
kg/day, kilogram/day, kilogr/day |
gram/day |
g/day |
g/day, gram/day, gr/day |
milligram/day |
mg/day |
mg/day, milligram/day, milligr/day |
microgram/day |
µg/day |
µg/day, microgram/day, microgr/day |
nanogram/day |
ng/day |
ng/day, nanogram/day, nanogr/day |
picogram/day |
pg/day |
pg/day, picogram/day, picogr/day |
femtogram/day |
fg/day |
fg/day, femtogram/day, femtogr/day |
kilogram/kilogram |
kg/kg |
kg/kg, kilogram/kilogram, kilogram/kg, kg/kg bw |
gram/kilogram |
g/kg |
g/kg, gram/kilogram, gram/kg, gr/kg, g/kg bw |
milligram/kilogram |
mg/kg |
mg/kg, milligram/kilogram, milligram/kg, milligr/kg, mg/kg bw, G225A |
microgram/kilogram |
µg/kg |
µg/kg, microgram/kilogram, microgram/kg, microgr/kg, µg/kg bw |
nanogram/kilogram |
ng/kg |
ng/kg, nanogram/kilogram, nanogram/kg, nanogr/kg, ng/kg bw |
picogram/kilogram |
pg/kg |
pg/kg, picogram/kilogram, picogram/kg, picogr/kg, pg/kg bw |
Molar |
M |
M, mol/L |
millimolar |
mM |
mM, mmol/L |
micromolar |
µM |
uM, µM, umol/L |
nanomolar |
nM |
nM, nmol/L |
moles |
moles |
moles, Moles |
millimoles |
mmoles |
mmoles, mMoles |
micromoles |
µmoles |
umoles, uMoles |
nanomoles |
nmoles |
nmoles, nMoles |
gram/kilogram bodyweight/week |
g/kg bw/week |
g/kg bw/week, gram/kg bw/week, gr/kg bw/week, G218A |
milligram/kilogram bodyweight/week |
mg/kg bw/week |
mg/kg bw/week, milligram/kg bw/week, milligr/kg bw/week, G217A |
microgram/kilogram bodyweight/week |
µg/kg bw/week |
µg/kg bw/week, microgram/kg bw/week, microgr/kg bw/week, G216A |
nanogram/kilogram bodyweight/week |
ng/kg bw/week |
ng/kg bw/week, nanogram/kg bw/week, nanogr/kg bw/week, G215A |
picogram/kilogram bodyweight/week |
pg/kg bw/week |
pg/kg bw/week, picogram/kg bw/week, picogr/kg bw/week |
femtogram/kilogram bodyweight/week |
fg/kg bw/week |
fg/kg bw/week, femtogram/kg bw/week, femtogr/kg bw/week |
gram/gram bodyweight/week |
g/g bw/week |
g/g bw/week, gram/g bw/week, gr/g bw/week |
milligram/gram bodyweight/week |
mg/g bw/week |
mg/g bw/week, milligram/g bw/week, milligr/g bw/week |
microgram/gram bodyweight/week |
µg/g bw/week |
µg/g bw/week, microgram/g bw/week, microgr/g bw/week |
nanogram/gram bodyweight/week |
ng/g bw/week |
ng/g bw/week, nanogram/g bw/week, nanogr/g bw/week |
picogram/gram bodyweight/week |
pg/g bw/week |
pg/g bw/week, picogram/g bw/week, picogr/g bw/week |
femtogram/gram bodyweight/week |
fg/g bw/week |
fg/g bw/week, femtogram/g bw/week, femtogr/g bw/week |
kilogram/week |
kg/week |
kg/week, kilogram/week, kilogr/week |
gram/week |
g/week |
g/week, gram/week, gr/week |
milligram/week |
mg/week |
mg/week, milligram/week, milligr/week |
microgram/week |
µg/week |
µg/week, microgram/week, microgr/week |
nanogram/week |
ng/week |
ng/week, nanogram/week, nanogr/week |
picogram/week |
pg/week |
pg/week, picogram/week, picogr/week |
femtogram/week |
fg/week |
fg/week, femtogram/week, femtogr/week |
Estimates nature types
Accepted Estimates nature types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Realistic |
Realistic |
For lognormal: no censoring at the value of the composite sample concentration, no upper limit to the unit concentration. For Beta: no censoring at the value of the composite sample concentration, unit values are never higher than the number of units in composite sample * value of composite sample concentration. |
|
Conservative |
Conservative |
For lognormal: unit values will be left-censored at the value of the composite sample concentration, no upper limit to the unit concentration. For Beta: unit values will be left-censored at the value of the value of composite sample concentration, unit are values never higher than the number of units in composite sample * value of composite sample concentration. |
Exposure approach types
Accepted Exposure approach types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Risk based (RPFs) |
Risk based (RPFs) |
Exposures are multiplied by the RPF and thus exposures to the different substances are on the same and comparable scale. |
|
Standardised |
Standardised |
All substances are standardised to equal variance, and the selection of the components will work on patterns of correlation only. |
Exposure method types
Accepted Exposure method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Manual |
Manual |
Exposure levels are determined by explicit specification. |
|
Automatic |
Automatic |
Exposure levels are generated automatically based on the estimated exposure distribution. |
Exposure route type
Accepted exposure routes how an individual is exposed to substance concentrations. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Dietary exposure |
Dietary |
Dietary |
Dietary exposure. |
Non-dietary oral exposure |
Oral |
Oral |
Non-dietary oral exposure. |
Non-dietary dermal exposure |
Dermal |
Dermal |
Non-dietary dermal exposure. |
Non-dietary inhalation exposure |
Inhalation |
Inhalation |
Non-dietary inhalation exposure. |
At target |
At target |
AtTarget |
Exposures directly at the target (organ). |
Exposure type
Accepted exposure types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Acute |
Acute |
Acute |
Acute exposure. |
Chronic |
Chronic |
Chronic |
Chronic exposure. |
Exposure unit
Accepted units for substance exposures. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
gram/kilogram bodyweight/day |
g/kg bw/day |
g/kg bw/day, g/kg/day, gram/kg bw/day, gr/kg bw/day, G212A |
milligram/kilogram bodyweight/day |
mg/kg bw/day |
mg/kg bw/day, mg/kg/day, milligram/kg bw/day, milligr/kg bw/day, G211A |
microgram/kilogram bodyweight/day |
µg/kg bw/day |
µg/kg bw/day, µg/kg/day, microgram/kg bw/day, microgr/kg bw/day, G210A |
nanogram/kilogram bodyweight/day |
ng/kg bw/day |
ng/kg bw/day, ng/kg/day, nanogram/kg bw/day, nanogr/kg bw/day, G214A |
picogram/kilogram bodyweight/day |
pg/kg bw/day |
pg/kg bw/day, picogram/kg bw/day, picogr/kg bw/day |
femtogram/kilogram bodyweight/day |
fg/kg bw/day |
fg/kg bw/day, fg/kg/day, femtogram/kg bw/day, femtogr/kg bw/day |
gram/gram bodyweight/day |
g/g bw/day |
g/g bw/day, g/g/day, gram/g bw/day, gr/g bw/day |
milligram/gram bodyweight/day |
mg/g bw/day |
mg/g bw/day, mg/g/day, milligram/g bw/day, milligr/g bw/day |
microgram/gram bodyweight/day |
µg/g bw/day |
µg/g bw/day, µg/g/day, microgram/g bw/day, microgr/g bw/day |
nanogram/gram bodyweight/day |
ng/g bw/day |
ng/g bw/day, nanogram/g bw/day, nanogr/g bw/day |
picogram/gram bodyweight/day |
pg/g bw/day |
pg/g bw/day, pg/g/day, picogram/g bw/day, picogr/g bw/day |
femtogram/gram bodyweight/day |
fg/g bw/day |
fg/g bw/day, fg/g/day, femtogram/g bw/day, femtogr/g bw/day |
kilogram/day |
kg/day |
kg/day, kilogram/day, kilogr/day |
gram/day |
g/day |
g/day, gram/day, gr/day |
milligram/day |
mg/day |
mg/day, milligram/day, milligr/day |
microgram/day |
µg/day |
µg/day, microgram/day, microgr/day |
nanogram/day |
ng/day |
ng/day, nanogram/day, nanogr/day |
picogram/day |
pg/day |
pg/day, picogram/day, picogr/day |
femtogram/day |
fg/day |
fg/day, femtogram/day, femtogr/day |
gram/kilogram |
g/kg |
g/kg, gram/kg, gr/kg, G015A |
milligram/kilogram |
mg/kg |
mg/kg, milligram/kg, milligr/kg, G061A |
microgram/kilogram |
µg/kg |
µg/kg, microgram/kg, microgr/kg, G050A |
nanogram/kilogram |
ng/kg |
ng/kg, nanogram/kg, nanogr/kg, G077A |
picogram/kilogram |
pg/kg |
pg/kg, picogram/kg, picogr/kg, G081A |
femtogram/kilogram |
fg/kg |
fg/kg, femtogram/kg, femtogr/kg |
gram |
g |
g, gram, gr, G148A |
milligram |
mg |
mg, milligram, milligr, G155A |
microgram |
µg |
µg, microgram, microgr |
nanogram |
ng |
ng, nanogram, nanogr, G120A |
picogram |
pg |
pg, picogram, picogr, G125A |
femtogram |
fg |
fg, femtogram, femtogr |
Focal commodity replacement method types
Accepted Focal commodity replacement method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Replace samples with focal commodity samples |
Replace samples with focal commodity samples |
Replace all samples of the selected focal commodity/commodities. |
|
Append focal commodity samples |
Append focal commodity samples |
Add the samples of the focal commodity/commodities to the background concentration data. |
|
Replace measurements of focal food/substance combinations with measurements from focal commodity samples |
Replace measurements of focal food/substance combinations with measurements from focal commodity samples |
Replace the substance concentrations of the background concentrations by substance concentrations from the focal commodity concentration data. |
|
Remove measurements of focal food/substance combinations |
Remove measurements of focal food/substance combinations |
Remove substance measurements for the selected focal food/substance combinations. |
|
Replace measurements of focal food/substance combinations with concentration limit value |
Replace measurements of focal food/substance combinations with concentration limit value |
Replace the substance concentrations of the background concentrations by a concentration limit value. |
Function types
Accepted Function types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Polynomial |
Polynomial |
A polynomial regression fits a nonlinear relationship between the value of the independent variable (e.g. age) and the corresponding conditional mean of y (here the exposure). A polynomial with a degree of 0 is simply a constant function; with a degree of 1 is a line; with a degree of 2 is a quadratic; with a degree of 3 is a cubic, and so on. |
|
Spline |
Spline |
A spline fits a nonlinear relationship between the value of the independent variable (e.g. age) and the corresponding conditional mean of y (here the exposure). A spline with a degree of 0 is simply a constant function; with a degree of 1 is a line; with a degree of 2 is a quadratic; with a degree of 3 is a cubic, and so on. |
Gender type
Accepted gender types. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
Female |
F |
Female, F |
Male |
M |
Male, M |
Harvest application type
Accepted harvest application types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Pre-harvest application |
Pre-harvest |
PreHarvest |
Pre-harvest application |
Post-harvest application |
Post-harvest |
PostHarvest |
Post-harvest application |
Hazard characterisation type
Accepted hazard characterisation types. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
Benchmark dose |
BMD |
BMD |
No observed adverse effect level |
NOAEL |
NOAEL |
Lowest observed adverse effect level |
LOAEL |
LOAEL |
Acceptable daily intake |
ADI |
ADI |
Acute reference dose |
ARfD |
ARfD |
No observed effect level |
NOEL |
NOEL |
Tolerable daily intake |
TDI |
TDI |
Tolerable weekly intake |
TWI |
TWI |
Benchmark dose lower confidence limit of 1% |
BMDL01 |
BMDL01 |
Benchmark dose lower confidence limit of 10% |
BMDL10 |
BMDL10 |
Human biomonitoring guidance values |
HBMGV |
HBMGV |
Other |
Other |
Other |
Hazard dose imputation method types
Accepted Hazard dose imputation method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Munro P5 (TTC approach) |
Munro P5 (TTC approach) |
Use the P5 of the Munro NOEL collection. |
|
Munro central value |
Munro central value |
Use an unbiased nominal value from the Munro NOEL collection; draw randomly from this collection in the uncertainty runs. |
|
Available hazard characterisations distribution P5 |
Available hazard characterisations distribution P5 |
Use the P5 of the available points of departure. |
|
Available hazard characterisations distribution central value |
Available hazard characterisations distribution central value |
Use an unbiased nominal value from the collection of available points of departure; draw randomly from this collection in the uncertainty runs. |
Health effect types
Accepted Health effect types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Risk |
Risk |
Health effect is negative (risk). |
|
Benefit |
Benefit |
Health effect is positive (benefit). |
Individual property type
Accepted individual property types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Categorical |
Categorical |
Categorical |
Categorical e.g. blood type A, B, AB, O or region East, West, North, South. |
Boolean |
Boolean |
Boolean |
Boolean e.g. yes, no, true, false. See Boolean types unit definitions. |
Numeric |
Numeric |
Numeric |
Numeric, real numbers. |
Nonnegative |
Nonnegative |
Nonnegative |
Nonnegative real numbers, positive or zero. |
Integer |
Integer |
Integer |
Integer, integer numbers. |
NonnegativeInteger |
NonnegativeInteger |
NonnegativeInteger |
NonnegativeInteger integer numbers, positive or zero. |
Month |
Month |
Month |
Month. See Month types unit definitions. |
DateTime |
DateTime |
DateTime |
DateTime, period. |
Gender |
Gender |
Gender, Sex |
Gender, sex or sexuality. See Gender types unit definitions. |
Location |
Location |
Location |
Location, country. |
Individual subset types
Methods for selecting/matching survey individuals with a specified/scoped population.
Name | Short name | Aliases | Description |
---|---|---|---|
Match individuals selection to population definition |
Match to population definition |
Match individuals selection to population definition. |
|
Ignore population definition (use all individuals in survey |
Ignore population definition |
Ignore population definition (use all individuals in survey). |
|
Match individuals selection to population definition using selected properties only |
Match using selected properties |
Match individuals selection to population definition using selected properties only. |
Intake model types
Accepted Intake model types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Observed Individual Means |
OIM |
Observed Individual Means: just the empirical means over the observed days. |
|
BetaBinomial Normal |
BBN |
BetaBinomial distribution for frequency of exposure + (transformed) Normal distribution for amounts (de Boer et al. 2009). |
|
Logistic-Normal Normal |
LNN0 |
Logistic-Normal distribution for frequency of exposure + (transformed) Normal distribution for amounts. |
|
Logistic-Normal Normal with correlation |
LNN |
Logistic-Normal distribution for frequency of exposure + (transformed) Normal distribution for amounts. Both models are estimated taking into account the correlation between exposure frequency and amounts. |
|
Iowa State University Foods model |
ISUF |
Iowa State University Foods model: semiparametric distribution for frequency of exposure + (transformed) Normal distribution for amounts (de Boer et al. 2009, Dodd (1996)). |
Internal concentration types
Accepted Internal concentration types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Internal modelled concentrations |
Internal modelled concentrations |
Internal modelled concentrations from dietary and/or non-dietary routes, aggregated. |
|
Human monitoring concentrations |
Human monitoring concentrations |
Human monitoring concentrations as measured in blood, urine or other compartments. |
Internal model type
Accepted internal model types. PBK model or absorption factor model Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Absorption Factor Model |
AbsorptionFactorModel |
AbsorptionFactorModel |
Use absorption factor model. |
PBK Model |
PBKModel |
PBKModel |
Use PBK model. |
Mean value correction types
Accepted Mean value correction types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Unbiased |
Unbiased |
The mean of the lognormal is unbiased (bias correction). |
|
Biased |
Biased |
The mean of the lognormal is biased (no bias correction). |
Measurement result type
Specifies the type of a measurement result. E.g., a positive value, a non-detect, or missing value.
Name | Short name | Aliases | Description |
---|---|---|---|
VAL |
VAL |
VAL |
Positive measurement greater than zero. |
LOD |
LOD |
LOD |
Measurement below the limit of detection (LOD). |
LOQ |
LOQ |
LOQ |
Measurement below the limit of quantification (LOQ). |
MV |
MV |
MV |
Missing value (MV). |
Missing value imputation method types
Accepted Missing value imputation method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Set zero |
Set zero |
Set missing values to zero. |
|
Impute from data |
Impute from data |
Replace missing measurements by random other measurements of the same substance, biological matrix and sampling type. |
|
No missing value imputation |
No missing value imputation |
No missing value imputation, all missing values remain in the data set and samples with missing values will be removed before analysis. |
Modelled foods calculation source types
Accepted Modelled foods calculation source types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Derive modelled foods from concentrations |
DeriveModelledFoodsFromSampleBasedConcentrations |
Derive modelled foods from sample based concentration data. |
|
Derive modelled foods from single value concentrations |
DeriveModelledFoodsFromSingleValueConcentrations |
Derive modelled foods from single value concentrations. |
|
Derive modelled foods from concentration limits |
UseWorstCaseValues |
Derive modelled foods from concentration limits. |
Month type
Accepted months types. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
January |
Jan |
Jan, Januari, 1 |
February |
Feb |
Feb, Februari, 2 |
March |
Mar |
Mar, 3 |
April |
Apr |
Apr, 4 |
May |
May |
May, 5 |
June |
Jun |
Jun, June, 6 |
July |
Jul |
Jul, July, 7 |
August |
Aug |
Aug, 8 |
September |
Sep |
Sep, Sept, 9 |
October |
Oct |
Oct, 10 |
November |
Nov |
Nov, 11 |
December |
Dec |
Dec, 12 |
Multiple substance handling method types
Accepted Multiple substance handling method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Combined assessment of selected substances |
Combined |
Combined assessment of selected substances. |
|
Loop over selected substances |
Loop |
Loop over selected substances. |
Network analysis type
Accepted Network analysis types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
No network analysis |
No network analysis |
No network analysis is applied. |
|
Apply network analysis |
Apply network analysis |
Network analysis is applied on the substance x component (U) matrix. |
Non-quantifications handling method types
Accepted Non-quantifications handling method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
By zero |
By zero |
Non-quantifications are assumed to be zero’s (set to 0). |
|
By f * LOR |
By f * LOR |
Non-quantifications are replaced by f * LOR where f is a constant. |
|
By f * LOD or by LOD + f * (LOQ - LOD) |
By f * LOD or by LOD + f * (LOQ - LOD) |
Left censored are replaced by f * LOD; Non-quantifications are replaced by LOD + f * (LOQ - LOD), where f is a constant. |
Nondetect imputation method types
Accepted nondetect imputation method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Replace by LOR/LOQ/LOD |
ReplaceLimit |
Non-quantifications are replaced by f * LOR or f * LOD or by LOD + f * (LOQ - LOD) where f is a constant. |
|
Impute from censored lognormal distribution |
Impute from censoredln |
Replace nondetect measurements by a random draw from the lower (left) tail of the censored lognormal distribution. |
Occurrence patterns tier types
Accepted Occurrence patterns tier types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Custom |
Custom |
By setting this tier to custom, the occurence model can be configured in any way desirable (without tier specific presets). The model is fully specified by the user. Both EFSA 2012 Optimistic and EFSA 2012 Pessimistic can be specified using the custom model choice. This choice allows for a sensitivity analysis where each factor is varied, one at the time. |
|
EC 2018 Tier 1 |
ComTier1 |
A test tier with realistic model settings. |
|
EC 2018 Tier 2 |
ComTier2 |
A test tier with realistic model settings. |
Point of departure type
Accepted point of departure types. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
Benchmark dose |
BMD |
BMD |
No observed adverse effect level |
NOAEL |
NOAEL |
Lowest observed adverse effect level |
LOAEL |
LOAEL |
No observed effect level |
NOEL |
NOEL |
Median lethal dose |
LD50 |
LD50 |
Benchmark dose lower confidence limit of 1% |
BMDL01 |
BMDL01 |
Benchmark dose lower confidence limit of 10% |
BMDL10 |
BMDL10 |
Point of departure types
Accepted Point of departure types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Unspecified (no conversion to common expression type) |
FromReference |
Do not convert non-standard point of departures. |
|
BMD (convert all hazard characterisations as BMDs) |
BMD |
Convert all point of departures to bench mark doses. |
|
NOAEL (convert all hazard characterisations as NOAELs) |
NOAEL |
Convert all point of departures to NOAELs. |
Processing distribution type
Accepted processing distribution types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Logistic Normal distribution |
LogisticNormal |
LogisticNormal, 1 |
Logisticnormal distribution. |
Log Normal distribution |
LogNormal |
LogNormal, 2 |
Lognormal distribution. |
Property level type
Accepted property level types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Individual |
Individual |
Individual |
Individual level. |
IndividualDay |
IndividualDay |
IndividualDay |
IndividualDay. |
Response type
Accepted response types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Continuous multiplicative |
CM |
ContinuousMultiplicative |
Response values are positive real numbers, e.g., weight, size. |
Continuous additive |
CA |
ContinuousAdditive |
Response values are real numbers, e.g., weight change, temperature. |
Binary |
B |
Binary |
Response values have binary outcomes (yes/no, true/false, success/failure, 0/1, etc.). |
Quantal |
Q |
Quantal, Binomial |
Response is measured in terms of number of successes out of N possible. |
Quantal group |
QG |
QuantalGroup |
Individual responses are measured as binary values, which may be grouped to form a quantal response. |
Count |
C |
Count |
Number of items (cells, molecules, deaths, etc.) in given interval/area/volume. |
Ordinal |
O |
Ordinal |
Relative scores (or graded scores) useable only for ranking. |
Risk metric types
Accepted Risk metric types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Margin of exposure |
MOE |
Margin of exposure (MOE). |
|
Hazard index |
HI |
Hazard index (HI). |
Single value dietary exposures calculation method types
Accepted Single value dietary exposures calculation method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
IESTI |
IESTI |
IESTI. |
|
IESTI new |
IESTI new |
IESTINew. |
|
TMDI |
TMDI |
Theoretical Maximum Daily Intake. |
|
IEDI |
IEDI |
International Estimated Daily Intake. |
|
Rees–Day model (I) |
Rees–Day(I) |
Rees–Day model (I). |
|
Rees–Day model (II) |
Rees–Day (II) |
Rees–Day model (II). |
Single value risk calculation method types
Accepted Single value risk calculation method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
From single value dietary exposures |
From single value dietary exposures |
From single value dietary exposures and hazard characterisations. |
|
As percentile from risks distribution |
As percentile |
As percentile from risks distribution. |
Substance group selection method types
Accepted Substance group selection method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
All substance |
IncludeAll |
Include all substances of the substances table and use hazard characterisation imputation for missing hazard data. |
|
Restrict to available hazard data |
RestrictHazardDoseRpf |
Restrict to the substances with available hazard data (either in the form of dose response models or RPFs). |
|
Restrict to available hazard data and possible membership |
RestrictHazardDoseRpfAndProbableMembership |
Consider only the substances with available hazard data and non-zero membership (i.e., P(AG) > 0). |
|
Restrict to available hazard data and certain membership |
RestrictHazardDoseRpfAndCertainMembership |
Consider only substances with certain assessment group membership (i.e., P(AG) = 1) and for which a hazard characterisation is available. |
|
Restrict to non-zero membership |
RestrictProbableMembership |
Consider all substances, use TTC based on the Cramer class for the substances for which no limit dose or RPF is defined. |
|
Restrict to certain membership |
RestrictCertainMembership |
Consider only the substances with certain assessment group membership (i.e., P(AG) = 1). |
Substance translation allocation method types
Accepted Substance translation allocation method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Random allocation |
Random allocation |
Random allocation. |
|
Allocate most potent |
Allocate most potent |
Allocate most potent active substance. |
|
Nominal estimate |
Nominal estimate |
Allocate nominal estimate (weighted average allocation). |
|
Allocate to all |
Allocate to all |
Allocate for each active substance independently as if all concentrations were allocated to this active substance. |
Target dose selection method types
Accepted Target dose selection method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Select most toxic |
MostToxic |
Choose the most toxic (default). |
|
Take aggregate |
Aggregate |
Choose an aggregated hazard characterisation when there there are multiple available candidates in nominal runs. |
|
Random draw |
Draw |
Draw a random hazard characterisation. |
Target doses calculation method types
Accepted Target doses calculation method types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
In-vivo PoDs (BMDs, NOAELs, etc.) |
InVivoPods |
In-vivo Points of Departures (BMDs, NOAELs, etc.). |
|
In-vitro BMDs |
InVitroBmds |
In-vitro Bench Mark Doses |
|
In-vivo PoDs for index substance, others using RPFs from in-vitro dose response models |
CombineInVivoPodInVitroDrms |
In-vivo Points of Departures for index substance, others using RPFs from in-vitro dose response models |
Target level type
Accepted units whether a dose is assumed to be an internal or external dose. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
External |
Ext |
Ext |
External exposure. |
Internal |
Int |
Int |
Internal exposure. |
Test system type
Accepted test system types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
In vivo |
In vivo |
InVivo |
In vivo |
Cell line |
Cell line |
CellLine |
CellLine |
Primary cells |
Primary cells |
PrimaryCells |
PrimaryCells |
Tissue |
Tissue |
Tissue |
Tissue |
Organ |
Organ |
Organ |
Organ |
Testing method types
Accepted xxx types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Backward |
Backward |
Backward selection starts with selecting a model with a function of the highest degree. Then, the degree of the function is decreased by one and the model is tested again. This process is repeated until decreasing the degree does not improve the model fit anymore. |
|
Forward |
Forward |
Forward selections starts with selecting a model with a function of the lowest degree. Then, the degree of the function is increased by one and the model is tested again. This process is repeated until increasing the degree does not improve the model fit anymore. |
Time unit
Accepted time units. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Hours |
h |
Hours, h |
In hours |
Minutes |
min |
Minutes, min |
In minutes |
Transform types
Accepted Transform types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Logarithmic |
Logarithmic |
Exposure amounts are transformed to normality using a logarithmic transformation. |
|
No transformation |
No transformation |
Exposure amounts are not transformed. |
|
Power |
Power |
Exposure amounts are transformed to normality using a Box-Cox power transformation. |
Uncertainty types
Accepted Uncertainty types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Empirical |
Empirical |
Data are taken as such. |
|
Parametric |
Parametric |
A parametric model is fitted to the data. |
Unit variability correlation types
Accepted Unit variability correlation types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
NoCorrelation |
NoCorrelation |
The unit residue values for unit portions (consumption amount/unitweight) are randomly drawn, explicitly ignoring any correlation between unit residues. |
|
FullCorrelation |
FullCorrelation |
The unit residue values for unit portions (consumption amount/unitweight) are randomly drawn, explicitly introducing correlation between unit residues, e.g. high (small) values occur more frequently together. |
Unit variability model types
Accepted Unit variability model types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Beta distribution |
Beta distribution |
Requires knowledge of the number of units in a composite sample, and of the variability between units (realistic or conservative estimates). Under the beta model, the simulated unit values are drawn from a bounded distribution on the interval. |
|
Lognormal distribution |
Lognormal distribution |
Requires only knowledge of the variability between units (realistic or conservative estimates). The lognormal distribution is considered as an appropriate model for many empirical positive concentration distributions (unbounded distribution). |
|
Bernoulli distribution |
Bernoulli distribution |
Requires only knowledge of the number of units in a composite sample (results are always conservative). The bernoulli model is a limiting case of the beta model, which can be used if no information on unit variability is available, but only the number of units in a composite sample is known |
Unit variability types
Accepted Unit variability types. Controlled terminology.
Name | Short name | Aliases | Description |
---|---|---|---|
Variation coefficient |
Variation coefficient |
Standard deviation divided by the mean. |
|
Variability factor |
Variability factor |
Defined as 97.5th percentile divided by the mean. |
Unit weight value type
Accepted unit weight types. Controlled terminology.
Name | Short name | Aliases |
---|---|---|
Unit weight raw agricultural commodity |
RAC |
RAC, UnitWeightRAC, UnitWeightRawAgriculturalCommodity |
Unit Weight edible portion |
EP |
EP, UnitWeightEP, UnitWeightEdiblePortion |
Value qualifier
Supported value qualifiers.
Name | Short name | Aliases |
---|---|---|
= |
= |
=, Equals |
< |
< |
lt, LessThan, < |