Stability Analysis for Elementary Characters of Hybrid Rice by AMMI Model
Bibliographic record
Abstract
A 3 site NCⅡ experiment was carried out for 45 hybrid rice varieties crossed by 5 CMS lines×9 Restorer lines, which are widely used recently. The characters′ performance in stability was analysed by AMMI model, and the results showed: (1) The G×E interaction were prominent; For yield and most characters environmental effect accounted for the most to the total variation, genotype and G×E interaction were on the 2nd and 3th orders respectively; But for 1000 grain weight, the effects of environment and genotype were equal. (2) The proportion of linear to non linear components in G×E interaction was varied with genotypes and characters. Some varieties or characters were mainly linear effect and others non linear effect. (3) No obvious contradiction existed between high yield and stability; It is possible to develop stable and high yield varieties. (4) AMMI model is an effective and accurate way for stability and adaptability measurement Comparatively, regression model is short in accurate and effectiveness.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".