Bibliographic record
Abstract
本研究采用ISSR分子标记技术百合的3个杂交组合[粉美(dark beauty)×精粹(elite),普瑞特(prato)×耀眼(cedeazzle),卷丹(Lilium lancifolium Thumb.)×多安娜(pollyanna)]的亲本及杂交一代(F1)进行遗传关系的检测,并且应用NTSYSpc2.0软件对其进行聚类分析,以筛选适合百合ISSR-PCR反应的最佳体系,并探讨杂交后代个体与其亲本间的亲缘关系与遗传特性。结果表明:从100条引物中中筛选出7条稳定多态的引物,共得到扩增位点95个,其中具有多态性共69个,多态性位点百分率达72.63%。从聚类图上可以看出杂交组合粉美×精粹与普瑞特×耀眼总体上先倾向于父本后倾向于母本,而卷丹×多安娜则总体上先倾向于母本后倾向于父本。
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".