The effect of treatment with long-acting antibiotic at postweaning movement on respiratory disease and on growth in commercial dairy calves
Bibliographic record
Abstract
Bovine respiratory disease (BRD) is a major concern when raising replacement heifers because of the high incidence and long-term effects of this disease, such as decreased growth and increased time to first calving. The objective of this study was to determine the effect of tulathromycin (TUL) treatment at postweaning movement on the incidence of BRD in dairy replacement heifers. A total of 1,395 heifers were enrolled between November 2006 and June 2007 at a commercial heifer-raising facility. Calves were randomly assigned either to treatment with TUL or to a positive control group treated with oxytetracycline (TET). Calves treated with TUL were 0.5 times (95% CI: 0.4 to 0.7) less likely to be treated for BRD in the 60 d following enrollment than calves treated with TET. For calves that had no history of BRD in the pre-enrollment period, TET calves weighed 4.9+/-0.5kg less than TUL calves after 6 wk in group housing. If calves were treated for BRD in the pre-enrollment period, there was no treatment effect on growth. Calves with clinical BRD in the 60 d following movement weighed 7.9+/-0.6kg less than calves without BRD after 6 wk in group housing. Treatment with TUL at the time of movement to group housing had a beneficial effect on the health and performance through the prevention of BRD in dairy calves with no prior history of the disease. Moreover, BRD after movement to group housing after weaning had a significant effect on the growth of dairy calves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".