Control of Growth of Disease-causing Microorganisms and Greenhouse Gas Emissions from Swine Operations using Zinc Oxide Nanoparticles
Bibliographic record
Abstract
The effectiveness of zinc oxide (ZnO) nanoparticles in reducing the levels of disease- causing microorganisms and greenhouse gas (carbon dioxide and methane) emissions in swine production operations was investigated in two fully instrumented and identical environmental chambers at the Prairie Swine Centre barn facility in Saskatoon. Each chamber housed 6 grower- finisher pigs. A ventilation air recirculation system was installed in each chamber; one chamber had a filter loaded with ZnO nanoparticles installed in the recirculation duct while the other chamber had filter pad only (not loaded with nanoparticles). Throughout the 15-day trial, the effect of ZnO nanoparticles on bioaerosols, greenhouse gases and pig performance was assessed. Results indicated that partial filtration of air in the chamber with a filter with zinc oxide nanoparticles in the ventilation recirculation system achieved reduction in bioaerosol concentrations at the exhaust stream and animal-occupied zone. In addition, the installation of air filtration system with ZnO nanoparticles in the chamber did not have any beneficial or adverse impact on carbon dioxide and methane emissions as well as on average daily gain and feed intake of pigs. Further studies using other deployment techniques will be conducted to provide a more comprehensive evaluation of the feasibility of nanoparticle application in swine facilities.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".