Assessment of the evolution of the proportion of respiratory and enteric pathogens and diseases in pre-weaned unvaccinated dairy heifers from Québec, Canada
Bibliographic record
Abstract
The objective of this study was to describe the proportion of enteric and respiratory pathogens and diseases in unvaccinated pre-weaned dairy heifers, in their first 2 weeks of life (exam 1), and at 4- to 8-weeks old (exam 2). Heifers from 20 dairy herds were examined and sampled twice for respiratory and enteric pathogens and diseases. Respiratory health score and ultrasonographic lung consolidation were assessed, and nasopharyngeal swabs, blood samples, and feces samples were collected. The prevalence for each disease and pathogen was described, and the difference between exams 1 and 2 was assessed. A total of 198 heifers were included at exam 1, and 182 of them were examined again at exam 2. At exam 1, the prevalence of respiratory diseases (positive clinical score or presence of lung consolidation) and diarrhea was 18% and 23%, respectively. At exam 2, the prevalence of respiratory diseases and diarrhea was 62% and 13%, respectively. Heifers were less likely to have respiratory diseases and pathogens at exam 1 than exam 2, and were more likely to have diarrhea at exam 1 than exam 2. These results help in understanding the dynamic of respiratory and enteric pathogens and diseases.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".