Size Distribution of Particulate and Associated Endotoxin and Bacteria in Traditional Swine Barn Rooms and Rooms Sprinkled With Oil
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.
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.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it