Identification of Risk Factors Associated with Treatment for BRD in Beef Calves Within the First 60 Days After Arrival at Fattening Operations in Northwestern Italy Beef Calves
Bibliographic record
Abstract
Bovine respiratory disease (BRD) impacts beef cattle health and farming systems. To better understand the BRD predisposing factors, a study was conducted in northwest Italy on a population of 26 batches (760 animals) of beef cattle imported from France. Of these, 173 underwent physical examination for clinical signs of BRD (rectal temperature > 39.5 °C, respiratory rate > 36 bpm, cough, nasal or ocular discharge) and blood sampling to detect antibodies against bovine viral respiratory infectious agents (e.g., parainfluenza 3, bovine herpesvirus type 1), haptoglobin and reactive oxygen metabolites concentrations, on arrival. Data on BRD treatments performed within 60 days of arrival were extracted from farm registers. The two most frequent cattle breeds were Blonde d'Aquitaine (80/173, 46.2%) and Limousine (61/173, 35.3%); the median batch weight was 332 kg (range, 195-470). At least one clinical sign of BRD was noted in 57.2% (99/173) of the animals. Most animals tested positive for BPIV3 (131/173, 75.7%) and BRSV (112/172, 64.7%). Bovine respiratory disease treatment was associated with transport time and average weight on arrival. Moreover, reactive oxygen metabolites levels differed between treated and untreated animals; this difference could help predict the onset of BRD, though further studies are needed to draw conclusions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".