Associations between health and productivity in cow-calf beef herds and persistent infection with bovine viral diarrhea virus, antibodies against bovine viral diarrhea virus, or antibodies against infectious bovine rhinotracheitis virus in calves
Bibliographic record
Abstract
OBJECTIVE: To measure associations between health and productivity in cow-calf beef herds and persistent infection with bovine viral diarrhea virus (BVDV), antibodies against BVDV, or antibodies against infectious bovine rhinotracheitis (IBR) virus in calves. ANIMALS: 1,782 calves from 61 beef herds. PROCEDURES: Calf serum samples were analyzed at weaning for antibodies against type 1 and type 2 BVDV and IBR virus. Skin biopsy specimens from 5,704 weaned calves were tested immunohistochemically to identify persistently infected (PI) calves. Herd production records and individual calf treatment and weaning weight records were collected. RESULTS: There was no association between the proportion of calves with antibodies against BVDV or IBR virus and herd prevalence of abortion, stillbirth, calf death, or nonpregnancy. Calf death risk was higher in herds in which a PI calf was detected, and PI calves were more likely to be treated and typically weighed substantially less than herdmates at weaning. Calves with high antibody titers suggesting exposure to BVDV typically weighed less than calves that had no evidence of exposure. CONCLUSIONS AND CLINICAL RELEVANCE: BVDV infection, as indicated by the presence of PI calves and serologic evidence of infection in weaned calves, appeared to have the most substantial effect on productivity because of higher calf death risk and treatment risk and lower calf weaning weight.
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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 | 0.003 |
| 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) | 0.002 | 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".