Web ware for cultivar grain yield evaluation and selection
Bibliographic record
Abstract
The variable weather conditions and climatic zones in western Canada often lead to differences in regional adaptation of cultivars that must be identified so that cropping risks can be reduced and returns maximized. Regional testing programs have been developed to provide a database for the determination of average grain yields for target areas, but in recent years the number of new cultivar releases has increased dramatically and the available resources for regional testing has been reduced. Attempts to deal with these problems have lead to web based systems that allow visitors to make head-to-head comparisons among cultivars of interest. However, the limitations associated with the comparison of means persist in these systems and considerable information of importance remains buried in the data files. This paper describes an interactive web-based model for head-to-head cultivar grain yield comparisons that calculates relative yields based on the growing season environmental potential at any prospective location in western Canada. By adapting and combining the databases from cooperative and provincial testing programs this decision-making tool also offers the opportunity to make plant breeding programs more effective while reducing the need for extensive post-registration regional testing.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.232 | 0.184 |
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".