Bibliographic record
Abstract
为了揭示新疆主栽海岛棉品种(系)的遗传差异，更好地指导新疆海岛棉育种，利用187对覆盖棉花全基因组的SSR引物对20个新疆海岛棉主栽品种(系)进行了遗传多样性分析。共有55对引物表现多态性，占总引物数的29.4%，共得到多态性位点97个，平均每对引物产生1.8个多态性位点。等位基因变异的多态性信息含量(PIC)在0.095~0.829之间，平均为0.560。成对品种间遗传相似系数在0.18~0.93之间，平均成对相似系数为0.44。聚类结果显示阈值为0.38时，20个品种(系)可分为两大类；在阈值为0.43和0.48时，两大类材料可分别分为两个亚类。本研究结果表明新疆主栽海岛棉品种(系)的遗传基础较宽，生产风险较小。
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".