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Record W2069193692 · doi:10.5864/d2015-003

Radon: public health professionals can make a difference

2015· article· en· W2069193692 on OpenAlexafffundvenueabout
Anne‐Marie Nicol, Karen Rideout, Prabjit Barn, Lydia Ma, Tom Kosatsky

Bibliographic record

VenueEnvironmental Health Review · 2015
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsBC Centre for Disease Control
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsRadonHealth professionalsPublic healthEnvironmental healthBusinessMedical educationMedicineNursingPolitical scienceHealth carePhysics

Abstract

fetched live from OpenAlex

Radon is a colourless, odourless, radioactive gas emitted naturally from uranium in Canadian rocks and soils. Outdoor concentrations of radon are almost always low, but levels can build up indoors, especially in the lower levels of a building, because radon gas is heavier than air. Once inhaled, the radioactive decay products of radon can adhere to cells lining the lungs and can lead to lung cancer. Health Canada cites radon gas exposure as the second leading cause of lung cancer in Canada, accounting for about 3000 deaths each year, and it is the leading cause of lung cancer among nonsmokers (Chen 2012). Fortunately, exposure to radon is preventable; levels in current structures can be reduced through mitigation, and new buildings can be constructed to prevent radon from entering in the first place.

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)0.006
metaresearch head score (Gemma)0.012
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.006
Open science0.0010.005
Research integrity0.0090.006
Insufficient payload (model declined to judge)0.0260.010

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 head0.324
GPT teacher head0.467
Teacher spread0.143 · 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
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

Citations6
Published2015
Admission routes4
Has abstractyes

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