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Record W2764065307 · doi:10.1093/rpd/ncx204

A REVIEW OF NATURAL RADIONUCLIDES IN CANADIAN DRINKING WATER (1975–16)

2017· review· en· W2764065307 on OpenAlexaffabout
Jing Chen, Michael W. Cooke, Jean‐François Mercier

Bibliographic record

VenueRadiation Protection Dosimetry · 2017
Typereview
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsHealth Canada
Fundersnot available
KeywordsRadionuclideEnvironmental scienceUraniumWater qualityPopulationEnvironmental healthNatural uraniumUranium mineGeographyHydrology (agriculture)MedicineEcologyEngineeringBiology

Abstract

fetched live from OpenAlex

Historical results of natural radioactivity in drinking water were reviewed for a total of 21 communities across Canada from 1975 to 2016. Analyses for 226Ra, 210Pb and total uranium were carried out on monthly composite samples of drinking water from selected Canadian municipalities. Generally speaking, levels of 226Ra, 210Pb and total uranium were found to be low compared to national and international standards for drinking water quality. Because levels were low, federal monitoring programs were discontinued in most communities in 1986 except for Regina, Elliot Lake and Port Hope. The population-weighted average levels for these three communities, using data from the most recent 5 years, are <1 mBq/L for 226Ra, <5 mBq/L for 210Pb and <0.4 μg/L for total uranium. The average effective dose resulting from drinking water intake at these levels would be <4.3 μSv per year.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.826
Threshold uncertainty score0.346

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0120.014
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.171
GPT teacher head0.457
Teacher spread0.286 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations11
Published2017
Admission routes2
Has abstractyes

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