Effects of Three Types of Free-Stall Surfaces on Preferences and Stall Usage by Dairy Cows
Bibliographic record
Abstract
One important criterion in choosing appropriate housing systems for dairy cattle is that the freestall provides a comfortable surface for the cow. This paper describes two experiments testing the effects of commonly used lying surfaces on stall preference and stall usage by Holstein cows. In both experiments, 12 cows were housed individually in separate pens. Each pen contained three free stalls with a different surface: deep-bedded sawdust, deep-bedded sand, and a geotextile mattress covered with 2 to 3 cm of sawdust. The animals were restricted to each surface in turn, in a random order for either 2 (Experiment 1) or 3 d (Experiment 2). Both before and after this restriction phase, the animals were allowed access to all three surfaces, and preference was determined, based on lying times. Of the 12 cows used in Experiment 1, 10 preferred sawdust before and nine after the restriction phase. During the restriction phase, average lying times and number of lying events during the restriction phase were significantly lower for the sand-bedded stalls (P < or = 0.05), and standing times were higher on mattresses (P < or = 0.05), compared with sawdust. Although these cows had some experience with all three surfaces during the experiment, they had been housed in sawdust-bedded stalls during their previous lactation. Cows used in Experiment 2 had spent their previous lactation in sand bedded stalls. In this experiment, about half the cows preferred sand and half sawdust, after the restriction phase. During the restriction phase of experiment, lying times and number of lying events were lower, and standing times were higher when the animals were restricted to the mattresses compared to either sand or sawdust (P < or = 0.05). These results indicate that (1) free stall surface can affect both stall preferences and stall usage, and (2) mattresses are less preferred.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".