Prophylactic Effects of Two Selective Dry Cow Strategies Accounting for Interdependence of Quarter
Bibliographic record
Abstract
Infusion of a long-acting antibiotic preparation at drying off in dairy cows as a prophylactic therapy is usually recommended for all quarters where it is in use. Studying the effectiveness of such treatment using quarter as the unit of analysis assumes that each quarter within a cow has a risk of being infected independent of the other quarters of the cow. Failure to account for interdependence of quarters within a cow may lead to inaccurate variance estimates and errors in assessing treatment effects. Data from two trials assessing different dry-cow strategies were examined for interdependence of infection between quarters. Logistic regression with a variance inflation factor or a multilevel analysis was used to assess the effect of antibiotic and internal teat-sealant dry cow strategies. Parity and infection status at drying off were covariates in the analysis. Interdependence of the risk of quarter infections within control-group cows was demonstrated in both dry-cow antibiotic and teat-seal trials. However, cows that received either of these treatments did not demonstrate interdependence. Treated quarters in both trials were 3.0 times less likely to acquire a new infection at calving compared with the untreated controls. Quarters in cows of parity 3 or greater were also at an increased risk in the antibiotic treatment trial. In both trials, quarters with either Corynebacterium spp. or coagulase-negative staphylococci infections at drying off had an increased risk of a new intramammary infection at calving. This study has demonstrated the beneficial and comparable effects of antibiotic and teat seal dry cow strategies; both decreased the risk of intramammary infection at calving. The application of dry-cow strategies at the cow level and not the quarter level is also supported.
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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 | 0.001 |
| 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) | 0.001 | 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".