Short communication: Effects of bedding quality on the lying behavior of dairy calves
Bibliographic record
Abstract
The lying behavior of adult cattle is strongly affected by characteristics of the lying surface, but no previous work has assessed the effects of lying surface for dairy calves. We evaluated how the lying behavior of dairy calves changed when calves were provided sawdust-bedded versus concrete lying surfaces, and in response to variation in dryness of the sawdust bedding. Five Holstein calves, approximately 2-wk old, were individually housed in pens with half of the lying surface bedded with kiln-dried sawdust [90% dry matter (DM)] and the other half with wet bedding varying in DM at 4 levels (74, 59, 41, and 29%) or bare concrete. All calves were tested on all 5 treatments, with treatment order assigned using a 5 × 5 Latin square. Total lying time averaged 17.2 ± 0.1 h/d and did not vary with treatment, but time lying on the wet bedding decreased from 5.3 ± 1.1 h/d at 74% DM to almost zero at 29%. Lying times on the side of the pen with dry bedding varied from 12.2 ± 1.2 h/d (when the wet bedding was 74% DM) to 16.8 ± 1.2 h/d (at 29% DM). Standing times were higher on the dry than the wet bedding (2.6 vs. 1.7 ± 0.1 h/d) but did not change across the range of bedding DM tested on the wet side. No calves ever lay down on the bare concrete. In conclusion, dairy calves showed clear preference for drier sawdust bedding and aversion to concrete lying surfaces, indicating that access to soft and dry bedding is important for growing calves.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".