A 99-year journey on the development of Canadian forages for livestock production
Bibliographic record
Abstract
Perennial forage, both grasses and legumes, are a critical component for ruminant livestock in Canada, being produced for both grazing and conserved feed. Canadian grasslands are a rich resource for cattle producers, particularly in the prairie region where the beef industry is largely located. Over the last 99 years, perennial forage breeding programs across the country have sought to improve and develop introduced forages to adapt to the Canadian climate and with particular tolerance to drought, diseases and, critically, enhanced winter survival. These long-term efforts have resulted in the release of approximately 171 cultivars (of which 75 were legumes and 96 were grasses). Of these grasses approximately 30 were tame and native cool-season species. These have helped maximise the productivity of prairie grasslands and enhance the sustainability of the beef sector in Canada. Breeding efforts continue today to further improve forage production to meet livestock needs and generate important ecosystem goods and services in an ever-changing climate.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.030 | 0.006 |
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".