Bibliographic record
Abstract
以夏枯草的叶片、茎节、顶芽为外植体在含不同浓度的6-BA和NAA的MS培养基中培养,比较其增值率和分化率。发现以茎节为外植体,诱导不定芽的最佳培养基为MS＋3.0mg/L6-BA＋0.1mg/L NAA,分化率为100%,增殖倍数为6.8。以顶芽为外植体,不定芽的最佳培养基为MS＋3.0mg/L6-BA＋0.05mg/LNAA或MS＋3.0mg/L6-BA＋0.1mg/LNAA,分化率分别为88.2%和84.6%,增殖倍数分别为5.8和6.2。最佳生根培养基为1/4MS＋NAA0.5mg/L,生根率为100%。将生根的组培苗经过驯化移栽后,成活率为93%。表明,叶片难以分化;茎节的分化率效果最好;顶芽的分化能力介于二者之间。
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".