Farming practices and the respiratory health risks of swine confinement buildings
Bibliographic record
Abstract
This study investigated whether clean swine confinement buildings (SCB) are less harmful to the respiratory system than older and dirtier facilities. Eight healthy volunteers were exposed for 4 h, at 1 week intervals, to eight SCB representing the widest possible range of cleanliness. Each volunteer and a technician rated the SCB for cleanliness from 1-10, 1 being the cleanest possible. Airborne dust, bacteria, endotoxin levels, molds, and ammonia were measured. For each volunteer measured, before and after each exposure, forced expiratory flows (forced expiratory volume in one second (FEV1), and forced vital capacity), white cells in nasal wash and venous blood, and nasal lavage levels of interleukin (IL)-8 and serum levels of IL-6. A methacholine challenge was obtained at baseline and following each exposure. Cleanliness scores ranged 1.5-8.25. Mean airborne levels were: dust 3.54 mg x m(-3) bacteria 4.25 x 10(5) CFU x m(-3); endotoxins 404 EU x m(-3); molds 883 CFU x m(-3); ammonia 20.7 parts per million (ppm). Expiratory flows decreased after exposure (FEV1 from 4.8+/-0.7 to 4.4+/-0.7, p<0.001), neutrophils in the nasal wash and white blood cells increased (28.5+/-37 to 424+/-207 x 10(3), 5.4+/-1.0 to 7.4+/-1.7 x 10(9) cells x mL(-1) respectively), IL-8 increased from 158+/-311 to 2679+/-639 pg x mL(-1), IL-6 from 0.15+/-0.26 to 2.34+/-0.92 pg x mL(-1), (p<0.001). All SCB were similarly harmful. In conclusion, modern farming has not succeeded in making swine confinement buildings inoffensive to exposed subjects.
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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 | 0.001 |
| 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) | 0.002 | 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".