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。
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".