Measuring the Feeding Behavior of Lactating Dairy Cows in Early to Peak Lactation
Bibliographic record
Abstract
The objectives of this study were to: 1) objectively define meal criteria (minimum interval between meals) of free-stall housed cows fed via a feed alley, 2) determine which measures of feeding behavior were most repeatable, and 3) describe changes in the feeding behavior from early to peak lactation. An electronic monitoring system was used to record individual cow presence (hits; 6-s resolution) at the feed alley for 21 lactating cows for three 8-d periods: period 1, 35 +/- 16 (mean +/- SD), period 2, 57 +/- 16, and period 3, 94 +/- 16 DIM. A mixture distribution model was used to calculate the meal criterion (27.74 min) by fitting the log10 frequency distribution of the intervals between hits. The within-cow repeatability was highest for feeding activity (hits d(-1)) and intensity (hits per meal min), moderate for total daily mealtime (min d(-1)) and meal duration (min meal(-1)), and lowest for meal frequency (meals d(-1)). From periods 1 to 2, all cows showed increases in total daily mealtime, meal frequency, and meal duration; however, cows with lower meal frequencies and feeding intensity in period 1 showed the greatest increases. Cows with high feeding activity and intensity during period 2 showed proportionally greater increases during period 3. These results illustrate that some measures of feeding behavior are highly repeatable within cows, but variable between cows and across stages of lactation. Thus, tests of treatment effects on feeding behavior should be within cow and control for days in milk.
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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) | 0.000 | 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".