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Record W7071155324

Seasonal variations in work-related health effects in swine farm workers

2016· other· en· W7071155324 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldComputer Science
TopicSeismology and Earthquake Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndoor bioaerosolLung functionSeasonalityFarm workersWork shiftShift workIncidence (geometry)
DOInot available

Abstract

fetched live from OpenAlex

The aim of the project was to investigate whether there were diminished health effects in swine farm workers during summer compared with winter, as seasonal differences in concentrations of bioaerosols have been reported. Twenty-four workers were visited once during each season. Before and after a work shift, they underwent lung function testing and blood sampling. During work, they wore personal air sampling equipment. The mean endotoxin exposure of the workers was highest during winter (25,690 vs. 6,553 EU/m(3); p = 0.004). Although exposures to endotoxin and CO(2) varied between the seasons, no differences in lung function were found between them. White blood cell concentration increased over the work shift from 5.74-6.82 in winter (p < 0.0001) and from 5.80-6.38 in summer (p = 0.014). These increases differed between the two seasons (p = 0.032). Plasma tumour necrosis factor concentrations fell over the work shift only during winter (1.34-1.24 pg/ml (p = 0.03) (p = 0.014 for the difference between seasons). Plasma interleukin-6 increased over the work shift independently of season (p = 0.0006). The study supported our hypothesis of adverse effects on lung function and immune system, but less so during summer than during winter among Quebec swine farm workers.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.603
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.008
GPT teacher head0.250
Teacher spread0.242 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2016
Admission routes1
Has abstractyes

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