Use of serologic evaluation for antibodies against bovine viral diarrhea virus for detection of persistently infected calves in beef herds
Bibliographic record
Abstract
OBJECTIVE: To determine whether use of serologic evaluation of a sentinel sample of calves or cows for antibodies against bovine viral diarrhea virus (BVDV) would accurately predict whether an animal persistently infected with BVDV could be detected in beef herds. SAMPLE POPULATION: 27 cow-calf herds in which the status of persistently infected calves was not known and 11 herds known to have persistently infected calves. Procedure-Detection of persistently infected calves was determined through immunohistochemical testing of tissue obtained at necropsy of all calves that died during calving season and skin (ear notch) specimens obtained from all young stock in the fall of 2002. Serum samples were collected from 30 spring-born calves and 10 mature cows. RESULTS: Optimum serologic test performance at time of weaning was detected when 10 calves were evaluated. At least 3 of 10 randomly selected calves were likely to have a titer > 1:1000 against BVDV type I or II in 53% of herds in which a persistently infected calf was detected during that year (sensitivity, 53%). However, at least 3 of 10 randomly selected calves were also likely to have a titer > 1:1000 in 20% of herds that did not have a persistently infected calf detected during that year (specificity, 80%). CONCLUSIONS AND CLINICAL RELEVANCE: Despite the use of a number of various cutoff values and sample sizes, serologic evaluation of a small number of calves or cows could not be used to accurately predict the presence of persistently infected cattle in a herd.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".