Bibliographic record
Abstract
用一套分别含有不同抗叶锈基因的53个以Thatcher为遗传背景的近等基因系（near-isogeniclines,NILs）对已报道的分别与抗叶锈基因Lr24和Lr35连锁的STS、SCAR进行特异性验证。结果对于与Lr24连锁的STS标记,在53个NILs中只在TcLr24亲本中扩增出片段大小与报道相同的310bp的条带,在TcLr35中也扩增出了一条片段,但片段大小不同于310bp约为270bp。对于与Lr35连锁的SCAR标记,只在TcLr35亲本中扩增出片段大小为900bp的条带,与报道片段大小一致。验证结果表明与抗病基因Lr24和Lr35连锁的STS、SCAR分子标记在NILs中特异性都较好,进一步证明了这两个分子标记可方便地用于小麦抗叶锈基因Lr24、Lr35的分子标记辅助选择育种。
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".