Seroprevalence of infection with Mycobacterium avium subspecies paratuberculosis, bovine leukemia virus, and bovine viral diarrhea virus in Maritime Canada dairy cattle
Bibliographic record
Abstract
The purpose of this study was to survey the seroprevalence of infection with the agents of production-limiting diseases in dairy cattle in New Brunswick, Nova Scotia, and Prince Edward Island. In 30 randomly selected herds per province, 30 cattle per herd were randomly selected and tested for antibodies to bovine leukemia virus (BLV) and Mycobacterium avium subspecies paratuberculosis (M. paratuberculosis), while 5 unvaccinated cattle over 6 months of age were tested for antibodies to bovine viral diarrhea virus (BVDV). For BLV, 20.8% (15.8% to 27.0%) of cows were positive, and 70.0% (60.3% to 79.7%) of herds had at least one positive cow. In BLV-positive herds, the average BLV prevalence was 30.9% (24.8% to 37.2%). For M. paratuberculosis, 2.6% (1.8% to 3.9%) of cows were positive, and 16.7% (8.8% to 24.5%) of herds had at least 2 M. paratuberculosis-positive cows. In M. paratuberculosis-positive herds, the average M. paratuberculosis prevalence was 8.5% (6.9% to 10.1%). For BVDV, 46.1% (35.5% to 56.7%) of herds had at least 1 BVDV-positive animal with a titer greater than or equal to 1:64.
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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 | 0.001 |
| 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".