Bibliographic record
Abstract
小麦PEBP-like基因与籽粒大小、粒重相关。本文根据水稻GS3基因序列搜索小麦及其近源种属EST序列，电子克隆小麦PEBP-like基因，并设计特异引物在万县百麦子／京411构建的重组自交系群体（recombinant inbred lines，RILs）鉴定该基因变异与籽粒大小及粒重的关系。结果表明，本文小麦籽粒大小与粒重相关性较好，其中粒宽和粒重的相关性最好（0．668^＊＊），其次是粒厚（0．629^＊＊），粒长也与粒重呈极显著正相关（0．485^＊＊）。WKS3—8引物在亲本和群体中多态性较好，具有A型等位基因的家系，籽粒较小、粒重低，其大部分家系干粒重低于平均值（38．3g）；而具有B型等位基因的家系，籽粒较大，粒重高，其大部分家系粒重高于平均值。上述说明PEBP-like基因等位变异与小麦粒长、粒宽、粒厚及粒重关系密切。
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".