Investigation of environmental factors and their effects on turkey health
Bibliographic record
Abstract
During the first stage of this study, a complete statistical analysis was performed on condemnation records from 1991-1997 at the four main processing plants in Ontario. Results of this part of the investigation indicated that airsacculitis was responsible for 14-36.5 percent of all condemnations, followed by cellulitis, which accounted for 14-21 percent of all condemnations. Toms showed a significantly higher condemnation rate (4.3 percent) than hens and broilers with 1.4 and 1.2%, respectively. Regarding airsacculitis, there was a significant difference of seasonal effect, being highest in winter and lowest in fall. In the second stage of this study, trends of important environmental factors (ammonia levels in air, litter moisture, relative humidity and temperature and total bacteria and 'E. coli' counts in the litter) at different ages and their effects on the condemnation rates due to airsacculitis and cellulitis were assessed. High concentrations of ammonia in the grower barn clearly increased the condemnation rates of airsacculitis in turkey flocks. Total 'E. coli' counts in the litter of the grower barn appeared to be an important factor in increasing the prevalence of cellulitis. It was also shown that lower levels of litter moisture and lower relative humidity had positive effects on the condemnation rates due to cellulitis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".