The Effects of Feed Bunk Competition on the Feed Sorting Behavior of Close-Up Dry Cows
Bibliographic record
Abstract
The objectives of this research were to describe the feed sorting, feeding behavior, and feed intake of cows consuming a close-up ration and to determine if these behaviors are affected by competition for access to the feed bunk. Thirty-six dry Holstein cows, consuming a close-up total mixed ration diet, were assigned to 1 of 2 treatments: 1) noncompetitive (1 cow/feed bin) or 2) competitive (2 cows/feed bin). Dry matter intake, feeding behavior, and sorting behavior were monitored for each feed bin on 4 separate days during wk 2 and 3 before the anticipated calving dates of the cows. Fresh feed and orts were sampled daily from each bin and were subjected to particle size analysis. The particle size separator consisted of 3 screens (18, 9, and 1.18 mm) and a bottom pan resulting in 4 fractions (long, medium, short, and fine). Sorting was calculated as the actual intake of each particle size fraction expressed as a percentage of the predicted intake of that fraction. Regardless of treatment, the cows sorted against long particles and for short and fine particles. Competition at the feed bunk had no effect on the sorting behavior, dry matter intake, or feeding time of the cows, but did dramatically increase the feeding rate of the cows. The competitively fed cows also had fewer meals per day, and tended to have larger and longer meals. Our results suggest that increased competition at the feed bunk promotes feeding behavior patterns that will likely increase the between-cow variation in composition of total mixed ration consumed.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".