Short Communication: Diurnal Feeding Pattern of Lactating Dairy Cows
Bibliographic record
Abstract
The objectives of this research were to: 1) describe the diurnal variation in feed alley attendance patterns of lactating dairy cows, 2) describe the sources of variation in these patterns, and 3) determine the effects of altering the feed push-up schedule on these patterns. An electronic monitoring system was used to record individual cow presence (6-s resolution) at the feed alley for 24 cows housed in a free-stall barn. Cows were subjected to 2 feeding schedules: 1) baseline schedule, where cows were fed at 0600 and 1515 h and feed was pushed closer to the cows at 1100 and 2130 h; and 2) experimental schedule, where 2 additional feed push-ups at 0030 and 0330 h were added to the baseline schedule. With the data collected from the monitoring system, description of the feed alley attendance patterns on a per minute basis of the group of cows was undertaken. Feed alley attendance was consistently higher during the day and early evening compared with the late night and early morning hours. The greatest percentage of cows attending the feed alley was seen after the delivery of fresh feed and the return from milking. The addition of extra feed push-ups in the early morning hours did little to increase feeding activity. It can be concluded that milking and delivery of fresh feed had a much greater affect on the diurnal pattern of feed alley attendance than did the feed push-ups.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".