Growth trends in <i>Bos grunniens</i> (yak) raised in pasture-based systems in Eastern Kentucky
Bibliographic record
Abstract
Bos grunniens (yak) are a unique ruminant species adapted to the rugged, high-altitude regions of Asia that could diversify livestock production in the Southeastern United States, however, limited research has been conducted on the yak in North America. The objective of this study was to evaluate the performance of male and female growing yaks in pasture-based systems in the mixed humid transition zone of the United States. Six males (beginning weight 132.8 ± 13.5 kg) and six females (beginning weight 124.3 ± 34.4 kg) were grazed in Year 1, and four males (beginning weight 157.3 ± 15.0 kg) and four females (beginning weight 160.9 ± 26.4 kg) were grazed in Year 2, allowing two pasture replicates per sex. Pastures were monitored throughout the study to assess forage availability, botanical composition, and nutritive value. In Year 1, males gained at a greater rate than females (0.45 kg/day vs. 0.23 kg/day; p < 0.01). In Year 2, a similar difference was observed for seasonal gains between sexes with males gaining 0.61 kg/day and females gaining 0.25 kg/day ( p < 0.01). A significant year effect for growth rates of male yaks was seen (0.45 kg/day vs. 0.61 kg/day; p < 0.01) but not observed in females. Sex can impact weight gain in growing yaks raised in pasture-based systems with males gaining more rapidly than females.
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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 | 0.000 | 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) | 0.001 | 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".