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Record W2147686104 · doi:10.1680/jees.2014.9.1.4

Bioaerosols in industrial environments: a review

2014· review· en· W2147686104 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2014
Typereview
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsIndoor bioaerosolBioaerosolEnvironmental scienceAir quality indexAerosolizationOccupational hygieneContaminationOccupational exposureWaste managementBiological hazardEnvironmental healthBusinessEnvironmental planningEnvironmental engineeringEngineeringOccupational safety and healthEcologyGeographyBiologyAerosolMedicine

Abstract

fetched live from OpenAlex

Air quality in workplaces is a main concern for industrial hygienists and occupational health specialists. Aerosolization of microorganisms or their by-products from contaminated material can significantly decrease the air quality and expose the workers’ health to potentially harmful effects. To identify the risks and elaborate safe exposure thresholds, the microbiology of air samples from industrial workplaces must be characterized, which means the airborne microorganisms must be identified and quantified. This review summarizes, for nonbiologist specialists, the principal sampling and analysis techniques for air sample characterization regarding microbiological contamination. A survey of the literature regarding levels of airborne bacteria, fungi, and viruses in agricultural industries, waste management plants, peat and wood processing facilities, and other industries is also provided. This review shows that very complex bioaerosol sources are present in industrial settings, and variable and hardly predictable biodiversity is expected in such environments.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.252
Teacher spread0.230 · 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