Dairy Heifer Motivation for Access to a Shaded Area
Bibliographic record
Abstract
= 18) were trained to push a weighted gate to access either an experimental area containing both a shaded (simple tree shade and shade cloth) and unshaded area (WITH SHADE) or an experimental area with no shade (BARREN). The latency to push the weighted gate, and the maximum weight pushed by each heifer, were recorded in both the summer and the autumn. Temperature and humidity were recorded continuously for the duration of the study and were used to calculate the heat index. The maximum weight pushed to enter the WITH SHADE area was greater in summer than in autumn, and was inversely related to the latency to push the weighted gate. Heifers refused to work for access to the BARREN environment. As expected, both the maximum ambient temperatures and heat index were higher in summer than in autumn, and also higher in the non-shaded areas than under the shade in both seasons. Heifers of higher social rank displaced other heifers more often, and spent more time in the shaded areas, particularly in the area with trees plus a shade cloth, than the intermediate and subordinate heifers. We conclude that shade is an important and valued resource for heifers reared on pasture-based systems in sub-tropical environments, particularly during the hot summer months.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.008 | 0.001 |
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".