Bovine viral diarrhea virus and virus-neutralizing antibody titers in beef calves at or near fall weaning.
Bibliographic record
Abstract
Objective: To estimate the prevalence of bovine viral diarrhea virus (BVDV) infection in spring-born beef calves, at or near fall weaning, and assess how concentrations of BVDV Type 1 and Type 2 antibodies near weaning varied among BVDV vaccination programs. Animals: Serum was collected from 1934 beef calves in 107 herds in the Canadian Cow-Calf Surveillance Network (C3SN). Procedure: Reverse transcription real-time polymerase chain reaction was used to detect BVDV infection, and serum virus neutralization assay measured antibody concentrations for BVDV Type 1 and Type 2. Records of BVDV vaccine use were available for nursing calves and cows within the past year from 95 herds. Mixed regression was used to estimate the association between herd vaccination status and antibody concentrations. Results: < 0.02) to have BVDV Types 1 and 2 titers ≥ 324 near weaning compared to unvaccinated calves. Conclusion and clinical relevance: Although the overall low prevalence of persistently infected calves was similar to that in previous reports, BVDV antibody titers were higher and the herd-level prevalence of BVDV infection was lower than in previous reports. Herd-level prevalence of BVDV infection was lower in Canadian beef herds that commonly administered BVDV vaccination to both cows and nursing calves. Calves from vaccinated herds also had significantly higher BVDV Type 1 and Type 2 titers at weaning, suggesting reduced risk from transient infection.
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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 | 0.000 |
| 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) | 0.001 | 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".