Bibliographic record
Abstract
利用分子标记辅助选择将广谱高抗稻瘟病的只蛳）基因和全生育期高抗白叶枯病的Xα23基因聚合到同一优良株系中，获得了含双基因的优良株系L10-L13。用来自不同地区的20个稻瘟病小种和中国流行的7个白叶枯病小种及安徽白叶枯病小种对聚合株系进行接菌鉴定，结果显示：聚合Pi9（t）和Xα23基因的株系L10-L13同时抗稻瘟病和白叶枯病：与稻瘟病的供体亲本75—1-127相比，抗性水平相当，均达抗级（R）水平，且抗谱相同；与白叶枯病的供体CBB23相比，对白叶枯病的抗性时期一致，均表现为全生育期抗性，而且抗性水平和抗谱相似。通过田间农艺性状的筛选，获得的双基因聚合系具有较好的农艺性状，可直接应用于生产或作为抗性亲本。
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".