Effects of Mixing on Drinking and Competitive Behavior of Dairy Calves
Bibliographic record
Abstract
Group housing provides increased access to space and social interactions for calves while reducing labor costs for producers. However, group housing necessarily requires that calves be mixed and no research to date has addressed the effects of mixing on behavior of milk-fed dairy calves. The objective of this study was to monitor the feeding and competitive behavior of individual dairy calves (n = 8) after introduction into an established group of older calves fed ad libitum by a computer-controlled milk feeder. Milk feeding was monitored for 2 d before introduction into the new group and both milk feeding and competitive behaviors were monitored for 4 d after mixing. Mean (+/- SE) milk consumption before mixing was 9.7 +/- 0.7 kg/d, dropped slightly on the day of mixing to 8.6 +/- 0.6 kg/d, but increased on d 1 to 3 after mixing to 11.1 +/- 0.3 kg/d. Calves visited the feeder less frequently on the day of mixing (6.0 +/- 1.8 visits/d) than on either the days before mixing (20.3 +/- 2.5 visits/d) or the days after mixing (25.3 +/- 6.9 visits/ d). The mean duration of feeder visits and mean milk consumption per visit increased from 4 min 15 s +/- 21 s and 0.53 +/- 0.06 kg per visit before mixing to 8 min 17 s +/- 1 min 28 s and 1.87 +/- 0.51 kg per visit on the day of mixing. Competitive displacements from the milk-feeding stall were rare. In summary, feeding behavior of young calves is altered on the day of mixing, but calves are able to maintain milk intake when using a milk feeder fitted with a stall that prevents calves from displacing one another.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".