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Record W3092127858 · doi:10.1007/s00411-020-00875-6

A discussion on the potential impact of residential radon exposure on the quality of exposure and risk assessment for former uranium miners

2020· article· en· W3092127858 on OpenAlexaff
Jing Chen

Bibliographic record

VenueRadiation and Environmental Biophysics · 2020
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsHealth Canada
Fundersnot available
KeywordsRadonRadon exposureEnvironmental healthRadiation exposureUraniumOccupational exposurePopulationEnvironmental scienceIndoor air qualityExposure assessmentToxicologyMedicineEnvironmental engineeringNuclear medicineBiology

Abstract

fetched live from OpenAlex

Epidemiological evidence of lung cancer risk from radon is based mainly on studies of underground miners where occupational exposures were, historically, relatively high in comparison to residential indoor exposure. However, radiation protection measures have caused radon levels in uranium mines to decrease significantly in more recent periods. Miners' occupational exposure is limited to their working years while they are exposed to environmental radon at home over their entire lifetime. Even during their limited working years, workers spend much more time at home than in workplaces. The biological effect of radon in mines cannot be distinguished from the biological effect of residential radon. Therefore, for an exposure-risk relationship study of former uranium miners, excess radon-induced lung cancer cases should be related to the combined radon exposure cumulated in workplaces and at homes in excess of the radon exposure of the reference population. This is especially important when residential radon levels differ or vary significantly between miners and the reference population over the course of extended follow-up years. This paper reviews some recent studies on former uranium miners, shares what seems controversial to the author and wonders whether lifetime exposure at home to widely varying radon concentrations can actually impact the quality of exposure assessment, and hence impact the results of the exposure-risk relationship.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.352
Teacher spread0.307 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2020
Admission routes1
Has abstractyes

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