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Record W3105513056 · doi:10.1088/1361-6498/abcae4

Evaluation of occupational radon exposure and comparison with residential radon exposure in Canada—a population-level assessment

2020· article· en· W3105513056 on OpenAlexaffabout
Jing Chen

Bibliographic record

VenueJournal of Radiological Protection · 2020
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsHealth Canada
Fundersnot available
KeywordsRadonRadon exposureEnvironmental healthOccupational exposureEnvironmental scienceEffective dose (radiation)MedicineToxicologyNuclear medicine

Abstract

fetched live from OpenAlex

Radon is a naturally occurring radioactive gas and presents everywhere on the Earth at varying concentration in workplaces and at homes. With Canadian labour statistics, time statistics and more than 7600 long-term radon measurements in workplaces, occupational radon exposure is evaluated for all 20 job categories based on North American Industry Classification System. Results are compared with residential radon exposure based on more than 22 000 long-term radon tests conducted in Canadian homes. The average annual effective dose due to radon exposure in workplaces is 0.21 mSv, which is lower than the average annual effective dose of 1.8 mSv from radon exposure at home by a factor of eight. Due to relatively higher radon concentration in residential homes and longer time spent indoors at home, exposure at home contributes to 90% of workers' total radon exposure (on average 1692 h in workplaces and 5852 h at homes). The analysis presented here is based on province-wide average radon exposures in various indoor and outdoor environments. Since the risk of developing lung cancer increases proportionally with increasing radon exposure, this evaluation indicates that on average reduction of radon levels in homes is very important and an effective way to reduce radon-induced lung cancers in Canada.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.068
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.309
GPT teacher head0.433
Teacher spread0.124 · 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

Citations5
Published2020
Admission routes2
Has abstractyes

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