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Record W4205776203 · doi:10.1016/j.jenvrad.2022.106811

Environmental monitoring and external exposure to natural radiation in Canada

2022· article· en· W4205776203 on OpenAlexaffabout
C. Liu, Mike Benotto, Kurt Ungar, Jing Chen

Bibliographic record

VenueJournal of Environmental Radioactivity · 2022
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsHealth Canada
Fundersnot available
KeywordsCosmic rayEnvironmental scienceRadiationBackground radiationPopulationEquivalent doseRadiation monitoringDose rateRadionuclideUraniumTerrestrial ecosystemPhysicsEcologyEcosystemNuclear physicsDemographyBiologyMedical physics

Abstract

fetched live from OpenAlex

K and decay products in the uranium and thorium decay series occurring in the ground. People are exposed to terrestrial radiation and cosmic rays everywhere and at all times. To assess Canadians' external exposure to natural radiation, five years (2016-2020) of real-time environment monitoring data recorded by Health Canada's Fixed Point Surveillance (FPS) network were analysed for 36 monitoring stations across Canada. Absorbed dose rates in air from terrestrial radiation vary geographically and seasonally. Absorbed dose rates due to cosmic rays depend strongly on the elevation and vary with solar activities. The population-weighted annual outdoor ambient dose equivalent rates are 20 nSv/h for terrestrial radiation and 52 nSv/h for cosmic rays. Considering that, on average, Canadians spend 89% of their time indoors and 11% of the time outdoors, the population-weighted annual effective doses were calculated as 443 μSv (54 μSv outdoors and 389 μSv indoors), with 20.6% (91 μSv) from terrestrial radiation and 79.4% (352 μSv) from cosmic rays.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.283
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2022
Admission routes2
Has abstractyes

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