The effects of turnout date to pasture on cattle weight gain
Bibliographic record
Abstract
The effects of multiple turnout dates on cattle weight gain were assessed in Nova Scotia in 1999 and 2000. Steers and heifers were released into pasture every 1 to 3 d from May 06 to May 28 in 1999 and from Apr. 26 to Jun. 05 in 2000. Cattle turned out to pasture later in the season gained less weight. Turnout date had a similar effect in both years, and 1 d of earlier turnout increased weight by 0.789 kg per animal over the summer. The time for cattle weight to recover after entering the pasture did not vary with turnout date, but it did differ significantly between years, with cattle recovering weight faster in 2000 than in 1999. Rate of weight gain decreased throughout the summer. The results suggest a mechanism for the turnout date effect: that cattle grow fastest on the pasture at the start of the season, and they grow faster on the pasture than in the barn. Thus, the earlier that they are introduced into the pasture, the more time they spend in the pasture during peak weight gain time. Rotational grazing maximizes the effect of turnout date by minimizing potential pasture degradation caused by early turnout. Key words: Pasture, cattle, rotational grazing, recovery period, turnout date, weight gain
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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 | 0.001 |
| 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".