The effect of respiratory disease and a preventative antibiotic treatment on growth, survival, age at first calving, and milk production of dairy heifers
Bibliographic record
Abstract
Bovine respiratory disease complex (BRD) is a common disease in weaned dairy calves that incurs economic and welfare costs. This study was an extension of a randomized clinical trial in which a single injection of tulathromycin (TUL) or oxytetracycline (TET) was administered at first movement to group housing for the prevention of BRD in the 60 d following antimicrobial treatment (BRD60). Calves treated with TUL were 0.5 times [95% confidence interval (CI): 0.4 to 0.7] as likely to be treated for BRD60 as calves treated with TET. The objectives of the current study were to evaluate the long-term effects of BRD and antibiotic treatment on growth of heifers until breeding age, age at first calving, incidence of dystocia, milk production, and mortality before first calving and mortality before 120 d in milk. At entry to the breeding barn (382 d of age), calves that experienced BRD60 weighed 16.0±2.3 kg less than calves that did not. Survival to first calving was recorded for 98% (1,343/1,392) of the heifers on this trial. For TET and TUL heifers with BRD60, 63% (94/150) and 73% (64/88) survived to first lactation, respectively. For TET and TUL calves without BRD60, 84% (436/517) and 84% (494/588) survived to first lactation, respectively. The median age at first calving for heifers with and without BRD60 was 714 (95% CI: 705-723) and 702 (95% CI: 699-705) days, respectively. Heifers with BRD60 were 1.5 (95% CI: 1.1-2.2) times more likely to have a calving ease score ≥2 at their first calving compared with heifers without BRD60. The administration of TUL at movement to group housing may have a role in the prevention of BRD and in mitigating some of the long-term effects of this disease.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".