Social Environment and Individual Differences in Feeding Behavior Are Associated with Risk of Endometritis in Dairy Cows
Bibliographic record
Abstract
Our aim was to determine whether individual differences in feeding and social behavior in different social environments affect health outcomes in dairy cows. We used eight groups of four animals per treatment assigned to either a ‘predictable’ or an ‘unpredictable’ and competitive social environment. Predictable cows were given free access to six feed bins with no change in feed delivery times; whereas, the unpredictable cows were required to share one feed bin with one resident cow and morning feed was delayed 0, 1, 2, or 3 h every other day. On alternate days, the unpredictable cows were also re-assigned to a new bin and a new resident partner. Low daily dry matter intake (DMI) was a risk factor for cytological endometritis in predictable cows (odds ratio (OR) (95% confidence interval): 0.17 (0.02, 0.53)), but low daily DMI was protective for unpredictable cows (OR: 1.93 (1.09, 4.14)). Although low rate of DMI (kg/min) was a risk factor for cytological endometritis for predictable cows (OR: 4.2 × 10−101 (8.6 × 10−206, 4.8 × 10−30)) it was unrelated to disease for unpredictable cows. There were no associations between feed bin visits or percentage of non-nutritive visits with the likelihood of cytological endometritis. This is the first evidence that individual differences in feeding behavior influence cytological endometritis risk in dairy cows, but the direction and magnitude of these effects is dependent on the social environment.
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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".