Replication Data for: The freestall reimagined: Effects on stall hygiene and space usage in dairy cattle
Bibliographic record
Abstract
Lying stalls for dairy cattle are designed to maintain cow hygiene, reduce labor associated with bedding maintenance, and provide cows with a comfortable place to lie down. These considera-tions can conflict: stall features that, e.g., reduce manure contamination of bedding can make the stall less comfortable, explaining why cows prefer lying in more open spaces. We developed an “alternative” lying area in which traditional freestalls (i.e., in which cattle are not confined to stalls but can move “freely” about the pen) were modified to create larger areas, and flexible stall partitions were included to help maintain cleanliness. We assessed cattle lying behaviour, in-cluding lying postures, in this alternative pen compared to both traditional freestalls and an open pack. Not surprisingly, cleanliness was higher in freestalls, but the alternative pen offered sub-stantial improvement in cleanliness over the open pack. There was little difference in postures as-sociated with lying positions (such as lying with limbs outstretched) between the open pack and alternative pen, and both offered greater limb extension compared to freestalls. We conclude that this type of alternative pen can provide producers with the opportunity to improve comfort com-pared to freestall housing and improve cleanliness compared to housing in an open pack.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.067 | 0.042 |
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".