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Slot: Per-Value Uncertainty Type (per_value_uncertainty_type)

Kind of per-value uncertainty captured in the column named by DataLayout.value_uncertainty_column (see envar_layout).

Tier: recommended

Why this slot matters

A "±" number means nothing until you know what kind of number it is: a standard error, a 95 % prediction interval, and an ensemble spread are not interchangeable and cannot be pooled or propagated the same way. Without the type, downstream code either mishandles the uncertainty or drops it, so exposure measurement error goes unaccounted for and health-effect estimates are biased, usually toward the null.

In plain terms

Every estimated value comes with a "how sure are we" number, but there are several different kinds. This says which kind you are looking at — for example a standard error (a ± number saying how far off the estimate could plausibly be) versus a prediction interval (a range the true value should fall inside, say 95 times out of 100).

URI: envar:slot/per_value_uncertainty_type

Applicable Classes

Name Description Modifies Slot
Uncertainty Uncertainty and quality character of a value series: per-value uncertainty ty... no

Properties

Type and Range

Property Value
Range UncertaintyTypeEnum
Domain Of Uncertainty

Cardinality and Requirements

Property Value

Examples

Value
standard_error
prediction_interval

See Also

Identifier and Mapping Information

Annotations

property value
tier recommended
justification A "±" number means nothing until you know what kind of number it is: a standard error, a 95 % prediction interval, and an ensemble spread are not interchangeable and cannot be pooled or propagated the same way. Without the type, downstream code either mishandles the uncertainty or drops it, so exposure measurement error goes unaccounted for and health-effect estimates are biased, usually toward the null.
explanation Every estimated value comes with a "how sure are we" number, but there are several different kinds. This says which kind you are looking at — for example a standard error (a ± number saying how far off the estimate could plausibly be) versus a prediction interval (a range the true value should fall inside, say 95 times out of 100).
covered_by None

Schema Source

Mappings

Mapping Type Mapped Value
self envar:per_value_uncertainty_type
native envar:per_value_uncertainty_type

LinkML Source

name: per_value_uncertainty_type
annotations:
  tier:
    tag: tier
    value: recommended
  justification:
    tag: justification
    value: 'A "±" number means nothing until you know what kind of number it is: a
      standard error, a 95 % prediction interval, and an ensemble spread are not interchangeable
      and cannot be pooled or propagated the same way. Without the type, downstream
      code either mishandles the uncertainty or drops it, so exposure measurement
      error goes unaccounted for and health-effect estimates are biased, usually toward
      the null.'
  explanation:
    tag: explanation
    value: Every estimated value comes with a "how sure are we" number, but there
      are several different kinds. This says which kind you are looking at — for example
      a standard error (a ± number saying how far off the estimate could plausibly
      be) versus a prediction interval (a range the true value should fall inside,
      say 95 times out of 100).
  covered_by:
    tag: covered_by
    annotations:
      omop_gaia:
        tag: omop_gaia
        annotations:
          extent:
            tag: extent
            value: absent
          status:
            tag: status
            value: asserted
          where:
            tag: where
            value: no column
          note:
            tag: note
            value: No gaia output carries a per-value uncertainty type.
      degauss:
        tag: degauss
        annotations:
          extent:
            tag: extent
            value: absent
          status:
            tag: status
            value: asserted
          where:
            tag: where
            value: no column
          note:
            tag: note
            value: DeGAUSS emits no per-value uncertainty.
      amadeus:
        tag: amadeus
        annotations:
          extent:
            tag: extent
            value: absent
          status:
            tag: status
            value: asserted
          where:
            tag: where
            value: no column
          note:
            tag: note
            value: Amadeus emits no per-value uncertainty type.
      cher:
        tag: cher
        annotations:
          extent:
            tag: extent
            value: absent
          status:
            tag: status
            value: asserted
          where:
            tag: where
            value: no column
          note:
            tag: note
            value: C-HER's column_tag Meta value can hold uncertainty columns in principle,
              but no per-value uncertainty type is a modelled field.
      codata:
        tag: codata
        annotations:
          extent:
            tag: extent
            value: out_of_layer
          status:
            tag: status
            value: asserted
          where:
            tag: where
            value: no column
          note:
            tag: note
            value: Per-value uncertainty is instance-layer; out of scope for CODATA.
description: Kind of per-value uncertainty captured in the column named by `DataLayout.value_uncertainty_column`
  (see envar_layout).
title: Per-Value Uncertainty Type
examples:
- value: standard_error
  description: Daymet daily Tmax reports a per-value standard error.
- value: prediction_interval
  description: ACAG satellite PM2.5 reports a per-value prediction interval.
from_schema: https://w3id.org/linkml/microschemas/envar
see_also:
- https://en.wikipedia.org/wiki/Standard_error
- https://en.wikipedia.org/wiki/Prediction_interval
rank: 1000
domain_of:
- Uncertainty
range: UncertaintyTypeEnum