Size Distribution of Particulate and Associated Endotoxin and Bacteria in Traditional Swine Barn Rooms and Rooms Sprinkled With Oil
Bibliographic record
Abstract
The objective of this pilot study was to investigate if a once-a-day sprinkling of canola oil in a swine confinement facility alters the airborne concentration and distribution of particulate matter and associated compounds (endotoxin and culturable microbes). Particulate was collected using an eight-stage cascade impactor in four identical swine grower/finisher rooms of a swine barn. Particulate (mg/m(3)) and endotoxin (EU/m(3) and EU/mg) distribution was determined. A six-stage viable cascade impactor was used to quantify total bacteria, enteric bacteria, and fungi. Microbes were characterized from subcultures prepared from the 10 most predominant colony types on each stage 3 (aerodynamic size 3.3-4.7μm) of the collection plates. Results indicated that oil sprinkling reduced total dust by 86% and total endotoxin concentration by 82.5%. However, the distribution patterns indicate that reduction is observed predominantly on large dust particles. In addition, the proportion of endotoxin associated with smaller particulate sizes (i.e., particles <4.7 μm) was higher in the oil-sprinkled rooms. Oil sprinkling does not markedly alter distribution of total bacteria, enteric bacteria, or fungi. The most frequently identified species were gram-positive genera. Oil sprinkling in swine confinement grower/finisher rooms can significantly reduce airborne total dust and endotoxin; however, smaller particles and associated endotoxin appear to remain in suspension, suggesting the overall improvement in air quality is uncertain. Further distribution studies and exposure outcome studies would need to be undertaken to determine the impacts of oil sprinkling.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".