Comparing antibiotic treatment at dry-off on one quarter versus all quarters in cows with only one quarter affected with a high somatic cell count or an intramammary infection
Bibliographic record
Abstract
<h2>Abstract</h2> The aim of this randomized controlled study was to evaluate, on cows with only one quarter affected at dry-off with an IMI, a high SCC (>200,000 cells/mL), or both, the impact of treating with an antibiotic plus internal teat sealant only the quarter affected (treating unaffected quarters with teat sealant alone; SelectAB) versus all quarters (AllAB) on subsequent lactation SCC (analyzed as log<sub>10</sub> transformed SCC) and IMI (odds of cure [i.e., affected quarter at dry-off but not at calving]; and odds of healthy [i.e., not affected at dry-off and calving]). Ninety-six multiparous cows from 3 research herds were randomly assigned to SelectAB or AllAB. Linear and logistic regression mixed models were used for data analysis. Cows assigned to AllAB had a 0.15 units lower log<sub>10</sub> SCC (95% CI=−0.19 to −0.11 log points) through the full subsequent lactation compared with SelectAB cows. The odds of cure for an affected quarter were similar for AllAB and SelectAB cows (odds ratio=0.77; 95% CI=0.27–2.20), but cows under AllAB had higher odds of having a healthy quarter shortly after calving compared with SelectAB cows (odds ratio=2.86; 95% CI=1.21–6.73). In conclusion, a reduced rate of healthy quarters (i.e., increased new infections any time from dry-off to shortly after calving), especially in quarters treated with internal teat sealant alone within an udder with one quarter affected with IMI, high SCC, or both at dry-off, may be a major barrier for the implementation of a quarter-based dry-off treatment approach.
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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 | 0.000 | 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".