Bibliographic record
Abstract
为明确四川近年来普通小麦的遗传差异情况，本研究采用微卫星分子标记（SSR）对四川省2005-2006年参加区试的66个小麦品系进行了遗传多样性研究，用18对扩增谱带稳定的SSR引物，共检测到106个等位位点，每对引物等位位点数为2～13个，平均5．89个。SSR引物的PIC介于0．22～0．91之间，平均多态性信息0．498。聚类分析表明，品种间遗传相似系数（GS）变异范围为0．390～0．834，平均值为0．608，品种间遗传相似性变幅较大，表明这次小麦区试品种（系）间存在着不同程度的遗传多样性差异。根据品种间遗传相似系数聚类，66份材料被聚成五类。
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".