Identifying Winter Hardy Alfalfa (Medicago sativa) for Northwestern Canada
Bibliographic record
Abstract
Winter kill is one of the most serious problems affecting alfalfa production in northwestern Canada. A rapid and accurate means of assessing winter hardiness is invaluable in developing new cultivars for this region. This program was designed to define some plant and environmental factors responsible for winter injury and to develop tests to identify plants with high yield potential and resistance to severe winter stress in northwestern Canada. The program has determined that the cold hardiness of alfalfa can change from year to year depending upon the plant and/or environmental conditions during the growing season. Three factors have been identified to be responsible for increasing the potential for winterkill: (1) low food reserves in the roots and crowns, (2) water saturated soil during the fall hardening period and (3) a late flush of growth in the fall from developing crown buds. A method was developed for separating the differences in winter hardiness between cultivars under field conditions. The method consisted of defoliating test plants at frequent intervals prior to winter then removing snow cover in early winter to induce a temperature stress. Germplasm sources from Ft. Smith and Ft. Providence in Canada's Northwest Territories (N. W. T.), two cultivars from the USSR (Taezhnaya and Krasnouphimskaya-6), and one synthetic from Beaverlodge (BL 78-5) demonstrated considerable potential for increased yield and persistence over adapted cultivars to reduce the effects of a stressfull winter environment on alfalfa production in northwestern Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".