Modifiable management practices to improve udder health in dairy cattle during the dry period and early lactation: A scoping review
Bibliographic record
Abstract
The objective of this scoping review was to characterize all available literature on modifiable management practices used during the dry period that have been evaluated for their effects on udder health in dairy cattle during the dry period and the subsequent lactation. Five databases and two conference proceedings were searched for relevant literature. Articles published in or after 1990 were eligible for inclusion. Eligible interventions or exposures were restricted to modifiable management practices; however, antimicrobial and teat sealant products were enumerated but not further characterized, as systematic reviews have been published on this topic. Other modifiable management practices were reported in 229 articles. Nutrition (n = 79), which included ration formulation and delivery (n = 44) and vitamin and mineral additives (n = 35), was the most commonly reported practice, followed by vaccines (n = 40) and modification of dry period length (n = 27). Risk of clinical mastitis (CM) was the most commonly reported outcome (n = 151); however, reporting of outcome risk periods varied widely between articles. Cure of existing intramammary infections (IMI) over the dry period (n = 40) and prevention of new IMI over the dry period (n = 54) were most commonly reported with a risk period between calving and 30 d in milk. Future systematic reviews with meta-analyses could target management practices such as nutrition, vaccines, and dry period length to quantify their effects on improving udder health during the dry period and early lactation. However, the variation in reporting of time at risk for CM and other outcomes challenges the ability of future synthesis work to inform management decisions on the basis of efficacy to cure or prevent IMI and CM. Consensus on which core outcomes should be evaluated in mastitis research and the selection of consistent risk periods for specific outcomes in animal trials is imperative.
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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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".