Investigation of the Role of Bovine Viral Diarrhea Virus (BVDV) in Undifferentiated Fever of Feedlot Cattle
Bibliographic record
Abstract
The undifferentiated fever (UF)/bovine respiratory disease (BRD) complex continues to be the single most important infectious disease entity in beef feedlot production. Current management practices have focused on successfully managing this disease complex through the use of prophylactic and therapeutic antimicrobial strategies, as well as vaccination programs targeting common viral and bacterial etiologic agents of feedlot UF/BRD described in the veterinary literature. In spite of these preventive and control strategies, there are substantial amounts of concrete and circumstantial epidemiologic, pathologic, serologic, and immunologic evidence that BVDV infection continues to play an important role in UF/BRD in commercial feedlot production, even though BVDV vaccination programs are in use. The purpose of the project reported herein was to improve our understanding of the role that BVDV plays in the pathogenesis of pen-level UF/BRD. The specific objectives of this study were: to describe the frequency and character (Type I or Type II) of BVDV infections both persistent infection (PI) and acute infection (AI)) at feedlot arrival and at the time of initial UF diagnosis; to investigate the effects of BVDV PI animals on pen-level animal health and feedlot performance; to investigate the effect of BVDV viremia on subsequent animal health outcome; and to describe the frequency of BVDV identification in postmortem tissue samples using immunohistochemistry.
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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 | 0.000 |
| 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 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".