Fodder oats in Nepal: Fulfilling farmer needs (part II)
Bibliographic record
Abstract
The introduction of winter fodder production to Nepal, based mainly on fodder oats, has been spectacularly successful as it has allowed improved animal nutrition and health, increased milk production and therefore farmer incomes, and reduced workloads (particularly for women). Seed of improved fodder oat varieties was originally introduced to Nepal in the 1980s, but unfortunately formal maintenance and seed multiplication of the selected varieties was not achieved. Since 2000, a novel New Zealand-based oat improvement initiative, coupled with the winter fodder production programme, has prompted renewed interest in this crop, and since 2004 six new varieties have been released based on parent material originally supplied from Canada, New Zealand and India. Under the new Cool Season Crop Improvement Programme-Nepal, an early generation seed maintenance and production nursery network is being established, linking research, extension and farmers. In this poster we briefly review the history of oat introductions, and provide a framework for the provision of genotypes that fulfill farmer needs for quick growing, high quality dry matter producing, multi-cut varieties.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.038 | 0.012 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.016 |
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; both teacher heads agree on what is shown here.
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".