Behavioral changes before metritis diagnosis in dairy cows
Bibliographic record
Abstract
Metritis is common in the days after calving and can reduce milk production and reproductive performance. The aim of this study was to identify changes in feeding and social behavior at the feed bunk, as well as changes in lying behavior before metritis diagnosis. Initially healthy Holstein cows were followed from 3 wk before to 3 wk after calving. Behaviors at the feed bunk were recorded using an electronic feeding system. Lying behavior was recorded using data loggers. Metritis, based upon the characteristics of vaginal discharge at d 3, 6, 9, 12 and 15 after calving, was diagnosed in 74 otherwise healthy cows. Behavior of these cows, beginning 2 wk before calving until the day of diagnosis, was compared with 98 healthy cows (never diagnosed with any health disorder, including ketosis, mastitis, and lameness) during the transition period. During the 2 wk before calving, cows later diagnosed with metritis had reduced lying time and fewer lying bouts compared with healthy cows. In the 3 d before clinical diagnosis, cows that developed metritis ate less, consumed fewer meals, were replaced more often at the feed bunk, and had fewer lying bouts of longer duration compared with healthy cows. We concluded that changes in feeding as well as social and lying behavior could contribute to identification of cows at risk of metritis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".