Adaptive framework for uncertainty analysis in electromagnetic field measurements.

Radiation protection dosimetry · 2015 · Unclear · Insufficient evidence

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UnclearInsufficient evidencePaper 4669

Study snapshot

PublicationRadiation protection dosimetry · 2015

Study typeexposure_assessment

Reported directionUnclear

Evidence ratingInsufficient

Abstract

Misinterpretation of uncertainty in the measurement of the electromagnetic field (EMF) strength may lead to an underestimation of exposure risk or an overestimation of required measurements. The Guide to the Expression of Uncertainty in Measurement (GUM) has internationally been adopted as a de facto standard for uncertainty assessment. However, analyses under such an approach commonly assume unrealistic static models or neglect relevant prior information, resulting in non-robust uncertainties. This study proposes a principled and systematic framework for uncertainty analysis that fuses information from current measurements and prior knowledge. Such a framework dynamically adapts to data by exploiting a likelihood function based on kernel mixtures and incorporates flexible choices of prior information by applying importance sampling. The validity of the proposed techniques is assessed from measurements performed with a broadband radiation meter and an isotropic field probe. The developed framework significantly outperforms GUM approach, achieving a reduction of 28% in measurement uncertainty.

Machine Enhanced Logic

AI evidence extraction

Structured fields below were generated from the paper’s abstract and metadata to make the evidence easier to inspect. Automated extraction may be incomplete or incorrect; verify important details against the original paper.

Study typeexposure_assessment

Effect directionunclear

PopulationNot supplied

Sample sizeNot supplied

ExposureNot supplied

Evidence strengthInsufficientConfidence: 74% · Peer reviewed: yes

Main findings

The paper proposes an adaptive framework for uncertainty analysis in EMF strength measurements that combines current measurements with prior knowledge using kernel-mixture likelihoods and importance sampling. Using measurements from a broadband radiation meter and an isotropic field probe, the framework reportedly outperformed the GUM approach, reducing measurement uncertainty by 28%.

Outcomes measured

Measurement uncertainty in EMF strength measurements
Performance vs Guide to the Expression of Uncertainty in Measurement (GUM) approach

View raw extracted JSON

{
  "study_type": "exposure_assessment",
  "exposure": {
    "band": null,
    "source": null,
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    "sar_wkg": null,
    "duration": null
  },
  "population": null,
  "sample_size": null,
  "outcomes": [
    "Measurement uncertainty in EMF strength measurements",
    "Performance vs Guide to the Expression of Uncertainty in Measurement (GUM) approach"
  ],
  "main_findings": "The paper proposes an adaptive framework for uncertainty analysis in EMF strength measurements that combines current measurements with prior knowledge using kernel-mixture likelihoods and importance sampling. Using measurements from a broadband radiation meter and an isotropic field probe, the framework reportedly outperformed the GUM approach, reducing measurement uncertainty by 28%.",
  "effect_direction": "unclear",
  "limitations": [],
  "evidence_strength": "insufficient",
  "confidence": 0.74,
  "peer_reviewed_likely": "yes",
  "keywords": [
    "electromagnetic field measurements",
    "uncertainty analysis",
    "GUM",
    "kernel mixtures",
    "importance sampling",
    "broadband radiation meter",
    "isotropic field probe"
  ],
  "suggested_hubs": []
}

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AI-extracted fields are generated from the abstract and metadata and may be incomplete or incorrect. This material is for informational purposes and is not medical advice.

Identifiers and source

DOI: 10.1093/rpd/ncu260
PubMed: 25143178

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