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Slot: Model Aggregate Uncertainty (model_aggregate_uncertainty)

Summary statistics for the model as a whole — cross-validation metrics and where they are reported.

Tier: recommended

Why this slot matters

Per-value uncertainty is often absent, so the whole-model cross-validation summary (R², RMSE) is frequently the only quantitative handle on how accurate the product is. Without it an analyst cannot judge whether the exposure estimates are precise enough for the health question, and cannot compare the reliability of two products.

In plain terms

A report card for how well the model predicts reality overall, checked by holding some data back and seeing how close its guesses came — for example an R² near 1 means the model tracks the true values closely. It also records where those scores were published.

URI: envar:slot/model_aggregate_uncertainty

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 ModelAggregateUncertainty
Domain Of Uncertainty

Cardinality and Requirements

Property Value

Examples

Value
None

See Also

Identifier and Mapping Information

Annotations

property value
tier recommended
justification Per-value uncertainty is often absent, so the whole-model cross-validation summary (R², RMSE) is frequently the only quantitative handle on how accurate the product is. Without it an analyst cannot judge whether the exposure estimates are precise enough for the health question, and cannot compare the reliability of two products.
explanation A report card for how well the model predicts reality overall, checked by holding some data back and seeing how close its guesses came — for example an R² near 1 means the model tracks the true values closely. It also records where those scores were published.
covered_by None

Schema Source

Mappings

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

LinkML Source

name: model_aggregate_uncertainty
annotations:
  tier:
    tag: tier
    value: recommended
  justification:
    tag: justification
    value: Per-value uncertainty is often absent, so the whole-model cross-validation
      summary (R², RMSE) is frequently the only quantitative handle on how accurate
      the product is. Without it an analyst cannot judge whether the exposure estimates
      are precise enough for the health question, and cannot compare the reliability
      of two products.
  explanation:
    tag: explanation
    value: A report card for how well the model predicts reality overall, checked
      by holding some data back and seeing how close its guesses came — for example
      an R² near 1 means the model tracks the true values closely. It also records
      where those scores were published.
  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 cross-validation R²/RMSE for the source
              model (Tmax scenario emits no model-accuracy summary).
      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 whole-model cross-validation metrics.
      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 whole-model cross-validation metrics.
      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 carries no model cross-validation summary 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: Model-aggregate uncertainty is instance-layer; out of scope for
              CODATA.
description: Summary statistics for the model as a whole — cross-validation metrics
  and where they are reported.
title: Model Aggregate Uncertainty
examples:
- description: Cross-validated R² for ACAG satellite PM2.5 and its reporting DOI.
  object:
    cv_r2: 0.9
    reported_in: 10.1021/acs.est.1c05309
from_schema: https://w3id.org/linkml/microschemas/envar
see_also:
- https://en.wikipedia.org/wiki/Cross-validation_(statistics)
rank: 1000
domain_of:
- Uncertainty
range: ModelAggregateUncertainty
inlined: true