Feeding behavior and agonistic interactions at the feed bunk are associated with hyperketonemia and metritis diagnosis in dairy cattle
Bibliographic record
Abstract
Hyperketonemia and metritis are common in the weeks after calving. This study tested if feeding and agonistic behaviors before calving were associated with the development of hyperketonemia (HYK) and metritis after calving. Holstein cows on 5 commercial farms were monitored for HYK (as identified using a cow-side β-hydroxybutyrate test) and metritis (using visual and olfactory assessment of vaginal discharge); both tests were conducted twice a week for 2 wk. Based on this assessment, we selected a balanced sample of cows that remained healthy (no signs of illness; n = 20), cows diagnosed with either HYK (n = 20) or metritis (n = 20), and cows with both HYK and metritis (n = 20). Video recordings from the 8 wk before calving (scored every 2 wk for 90 min immediately after fresh feed delivery) were used to evaluate feeding behavior and competition at the feed bunk. Feeding behavior before calving was associated with postpartum diagnosis of HYK and metritis. Specifically, cows that spent less time eating had higher odds of HYK and metritis. Odds of remaining healthy (compared with becoming sick with at least 1 condition) increased by 1.3 times for every additional 15 min spent eating. Additionally, cows that were involved in fewer agonistic interactions prepartum were more likely to be diagnosed with both conditions during the postpartum period. Odds of remaining healthy (compared with becoming sick with at least one condition) increased by 1.9 times for every 6 additional interactions. We conclude that prepartum feeding and agonistic behaviors can be used to identify animals at risk of HYK and metritis postpartum.
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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 | 0.001 |
| 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".