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Record W2062095256 · doi:10.1002/ajim.20513

Cross‐shift peak expiratory flow changes are unassociated with respirable coal dust exposure among South African coal miners

2007· article· en· W2062095256 on OpenAlexaff
Rajen N. Naidoo, Thomas G. Robins, Margaret R. Becklake, Noah Seixas, Mary Lou Thompson

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2007
Typearticle
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsMcGill University
FundersMedical Research CouncilInyuvesi Yakwazulu-Natali
KeywordsMedicineCohortDemographyEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The objectives of this study were to determine whether cross-shift changes in peak expiratory flow rate (PEFR) were related to respirable dust exposure in South African coalminers. METHODS: Fifty workers were randomly selected from a cohort of 684 miners from 3 bituminous coalmines in Mpumalanga, South Africa. Peak expiratory efforts were measured prior to the commencement of the shift, and at the end of the shift on at least two occasions separated by at least 2 weeks, with full shift personal dust sampling being conducted on each occasion for each participant. Interviews were conducted, work histories were obtained and cumulative exposure estimates were constructed. Regression models examined the associations of cross-shift changes in PEFR with current and cumulative exposure, controlling for shift, smoking and past history of tuberculosis. RESULTS: There were marginal differences in cross-shift PEFR (ranging from 0.1 to 2 L/min). Linear regression analyses showed no association between cross-shift change in PEFR and current or cumulative exposure. The specific shift worked by participants in the study showed no effect. CONCLUSIONS: Our study showed no association between current respirable dust exposure and cross-shift changes in PEFR. There was a non-significant protective effect of cumulative dust exposure on the outcome, suggesting the presence of a "healthy worker survivor effect" in this data.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.325
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.298
Teacher spread0.258 · 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.

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

Citations4
Published2007
Admission routes1
Has abstractyes

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