Changes in land, feed, and manure management practices on beef operations in Canada between 2005 and 2011
Bibliographic record
Abstract
The objective of this paper was to evaluate changes in management practices of beef cattle from 2005 to 2011. Large nationwide surveys of husbandry practices in the beef industry were conducted to represent management practices used in 2005 and 2011 across Canadian Ecoregions. The two surveys attempted to similarly represent operation types (cow–calf, backgrounding, and finishing) and size. Several statistically significant changes in management practices from 2005 to 2011 were observed: in non-feedlot operations, these included more operations with >50% legume in perennial forage, less N fertilization applied to forages, increased winter grazing of cows, and higher quality feed used as a supplement to grazing. In feedlots, there were more shelter structures, less feeding of grain and more of high-legume forages, and more frequent removal of manure. Several practices remained constant in the two surveys including use of covers for storing hay, frequency of harvesting forage, time of barn and feedlot cleanout, manure storage and practices relating to manure incorporation into soil. The large increase in use of winter grazing on the Prairies as well as in eastern Canada documented here is an important change in the industry that has both economic and environmental implications.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".