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Record W4391891665 · doi:10.13031/aea.15720

Bioaerosols in Eastern Canadian Dairy Barns Using Tie- and Free-Stall Housing

2024· article· en· W4391891665 on OpenAlexafffundabout
Keven Bergeron, Florent Rossi, Valérie Létourneau, Araceli Dalila Larios, Stéphane Godbout, Sébastien Fournel, Caroline Duchaine

Bibliographic record

VenueApplied Engineering in Agriculture · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsUniversité LavalInstitut de Recherche et de Développement en AgroenvironnementInstitut universitaire de cardiologie et de pneumologie de Québec
FundersAgriculture and Agri-Food Canada
KeywordsStall (fluid mechanics)Indoor bioaerosolEnvironmental scienceEngineeringEnvironmental engineeringWaste managementGeographyMeteorologyAerospace engineering

Abstract

fetched live from OpenAlex

Highlights Building characteristics (ventilation and animal density) seem to have an important effect on air quality. Concentration in the air seems to be influenced by amounts in the bedding for certain air quality indicators. Dust concentrations were below OSHA threshold, while some barns exceeded DECOS threshold for endotoxins. This study gives new data into the biological components in the air of dairy barns (bacteria, molds, endotoxins, etc.) Free-stall or tie-stall housing may not be linked with poorer air quality. Abstract. Alternative farming methods make it possible to satisfy public demands for animal welfare while preserving production efficiency, with free housing in dairy farms being an example. The increased movement of cows may have a negative impact on air quality and the presence of etiological agents, increasing the prevalence of lung disease in workers. Free-stall farms, however, are more spacious and modern than tie-stall farms. This study characterizes air quality in free-stall and tie-stall farms (dust, total bacteria, Penicillium/Aspergillus, archaea, and endotoxins). It also focuses on detecting airborne etiological agents and indicators of fecal contamination, as well as assessing the effect of environmental factors on air quality. Five farms of each type (free housing and tie housing) using straw bedding material and equipped with mechanical ventilation were visited. Sampling visits were conducted in winter with no activity (e.g., bedding spreading) in buildings. Dust was evaluated using the DustTrakTM DRX Aerosol Monitor, and bioaerosols were sampled in triplicates for 10 minutes using the SASS®3100 Dry Air Sampler. Finally, soiled bedding was collected throughout the barn. No type of housing seems to be linked with poorer air quality, but some air quality indicators stood out in some outliers. The most recently designed free-housing buildings and the greater air volume may have played a role in the absence of detected differences. Escherichia coli, Enterococcus spp., Clostridium perfringens, Aspergillus fumigatus, Staphylococcus aureus, Saccharopolyspora rectivirgula, Coxiella burnetii, and Klebsiella pneumoniae were detected in high concentrations in both types of buildings. Soiled bedding concentrations, ventilation rates, and animal density seemed to have a significance on air quality in dairy barns. Keywords: Air Quality, Bioaerosols, Housing, Occupational exposure.

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)0.000
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 score0.123
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.183
Teacher spread0.177 · 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

Citations4
Published2024
Admission routes3
Has abstractyes

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