Bibliographic record
Abstract
根据斑茅ITS区序列设计编号为EF1/ER1和编号为EF2/ER2的两对引物,经在甘蔗及其近缘属植物间ITS-PCR扩增,证明这两对引物是斑茅特异引物,其中引物EF1/ER1在斑茅多态性研究中扩增出5种带型,而引物EF2/ER2扩增出3种带型;同时,利用这两对引物对甘蔗(拔地拉)与斑茅杂交的9个F1,甘蔗斑茅真实杂种(崖城96-66、96-46)与CP84-1198的36 个BC1以及崖城95-41与内江57-416的12个BC1,15个曾被认为具有斑茅血缘的品系进行分子鉴定,结果表明,两对引物的鉴定结果基本一致,其中对斑茅F1的分子鉴定结果与前人(沈万宽)的同工酶鉴定结果相一致,对15个曾被认为具有斑茅血缘的品系进行鉴定结果显示大部分品系为假杂种.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".