Bibliographic record
Abstract
This paper reviews recent data and concepts on metritis, purulent vaginal discharge (PVD), and endometritis in dairy cows and the ways in which these diseases affect reproductive performance. Metritis is characterized by fetid discharge from the uterus, with or without fever. Purulent vaginal discharge describes exudate that is >50% pus that may be attributable to uterine infection or cervicitis. Endometritis is inflammation of the uterus diagnosed by endometrial cytology with a proportion of neutrophils (typically ≥5%) that is associated with impaired fertility. Metritis and PVD are associated with uterine bacterial dysbiosis: changes in the microbiota to lesser diversity and greater abundance of pathogens, especially Gram-negative anaerobic bacteria, and Trueperella pyogenes in the case of PVD. Metritis is justifiably treated with approved antibiotics but criteria for more selective treatment without loss of performance are emerging. Purulent vaginal discharge is not synonymous with clinical endometritis, and greater precision in terminology is warranted. PVD is likely under-diagnosed and represents an opportunity for improved management in many herds. Endometritis seems in many cases to reflect persistent, dysregulated inflammation, for which the inciting cause is unclear. Postpartum uterine infection and inflammation have harmful effects on oocytes, embryo development, and the endometrium for at least three months, even if the disease is apparently resolved. Emerging concepts of the resolution and regulation of inflammation are promising for the improvement of prevention and therapy of endometritis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".