Invited review: The role of contagious disease in udder health
Bibliographic record
Abstract
Contagious diseases are a threat to animal health and productivity, both nationally and at the farm level. This makes implementation of biosecurity measures to prevent their introduction and spread within countries and farms a necessity. Mastitis is the most common and costly contagious disease affecting dairy farms in the western world. The major mastitis pathogens are endemic in most countries, and biosecurity measures to prevent introduction and transmission must therefore be implemented at farm level. The 40-yr-old mastitis control plan remains a solid foundation to prevent the spread of contagious intramammary infections. Contagious diseases that do not affect the mammary gland directly may have an indirect effect on mastitis. This is true for list A diseases such as foot and mouth disease, for which biosecurity measures may need to be taken at national level, and for other infections with nonmastitis pathogens such as bovine viral diarrhea virus and Mycobacterium avium ssp. paratuberculosis. Maintaining a closed herd decreases the risk of introduction of pathogens that affect udder health directly or indirectly. If animals are purchased, their udder health history should be evaluated and they should be examined and tested for contagious diseases. Transmission of infections by and to humans and nonbovine animals may occur. Contact with visitors and nonbovine animals should therefore be minimized. Because of globalization and heightened consumer awareness, the importance of biosecurity now supersedes individual farms, and increased pressure to control transmission of contagious diseases can be expected at industry or government levels in western countries and elsewhere.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 0.010 |
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".