Using an “Index of Merit” to Evaluate Winterhardy Pea Lines
Bibliographic record
Abstract
Winter feed pea (Pisum sativum ssp. arvense) might serve as a partial or complete replacement for fallow in the winter wheat-summer fallow (WW-SF) system with potential to integrate cereal and livestock production in the Central Great Plains (CGP). The objective of this study was to evaluate advanced winter pea lines bred in the Wyoming environment in comparison with existing winter feed pea cultivars that were bred elsewhere. Six elite lines, one a blend of two lines, and three check cultivars were compared for overall merit, based on yield for forage and seed, and in two different production systems, dryland and irrigated, and at two locations (Lingle WY and Laramie WY) during the 2010-2011 and 2011-2012 growing seasons. Indices of merit, calculated in two ways: a mean-adjusted index and a standardized index, were used to simultaneously evaluate lines/cultivars for forage and seed yield. Based on the results from both indices, five Wyoming-bred elite lines (one a blend of two lines) ranked in the top five lines of 10 lines/cultivars tested. Importantly, three Wyoming-bred lines (Wyo#11, Wyo#11 +Wyo#13, and Wyo#13) all ranked significantly higher for overall merit than any existing winter feed pea cultivar tested in this study: ‘Common’, ‘Specter’ and ‘Windham’. Because four measures of merit in the both indices are positively correlated no serious compromises or “trade-offs” are manifested among these four traits. This research shows that winter pea has potential value for forage and seed yield, mostly depending on growing season precipitation in the CGP.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".