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Record W1996587403 · doi:10.1097/jom.0b013e3182636e49

Prevalence of Chronic Bronchitis in Farm and Nonfarm Rural Residents in Saskatchewan

2012· article· en· W1996587403 on OpenAlexafffundabout
Punam Pahwa, Chandima Karunanayake, Philip Willson, Louise Hagel, Donna Rennie, Joshua Lawson, William Pickett, James A. Dosman

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsSaskatchewan Health AuthorityUniversity of Saskatchewan
FundersCanadian Institutes of Health ResearchAmerican Thoracic Society
KeywordsNonfarm payrollsChronic bronchitisEnvironmental healthMedicineBronchitisAsthmaObesityDemographyGerontologyAgricultureGeographyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the prevalence of chronic bronchitis (CB) and associated risk factors in farm and nonfarm rural residents in Saskatchewan, Canada. METHODS: The questionnaire collected information about health, contextual, and individual factors from 8261 farm and nonfarm adult residents (18 years and older). RESULTS: The prevalence of CB was 5.3% among farm residents and 6.4% among nonfarm residents. We found a greater prevalence of CB associated with household income adequacy, increasing age, allergies, history of lung disease in a parent, exposure to stubble smoke, obesity, prenatal exposure to smoking, and female sex. Smoking interacted with occupational exposure to wood dust and solvents, and allergic reaction to molds. CONCLUSION: The results suggest that increasing household income and reducing smoking could be primary, modifiable determinants of CB prevalence.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.213
Threshold uncertainty score0.429

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.012
GPT teacher head0.275
Teacher spread0.263 · 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 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

Citations15
Published2012
Admission routes3
Has abstractyes

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