Two types of biplots to integrate multi‐trial and multi‐trait information for genotype selection
Bibliographic record
Abstract
Abstract Genotype × environment interaction (GE) and unfavorable associations among breeding objectives are the two key challenges in genotype evaluation and selection. Dealing with GE includes utilizing repeatable GE and accommodating nonrepeatable GE, and analytical tools for both steps have been developed in recent years. The genotype by yield × trait (GYT) analysis was also developed to address the issue of genotype selection based on multiple traits. However, a method to integrate both multi‐trial and multi‐trait information has been lacking. The purpose of this study was to fill the gap. Two types of biplots were described and demonstrated, using an oat ( Avena sativa L.) dataset as an example. The G + GE biplot of GYT index graphically displays the mean and stability of the genotypes, considering all breeding objectives. The GYT biplot across trials graphically displays the overall superiority and the strengths and weaknesses of the genotypes, after accommodating the nonrepeatable GE. The two types of biplots rank the genotypes in the same order of superiority; they complementarily provide a complete picture of the genotypes and allow confident genotype evaluation, selection, and recommendation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".