Preliminary Study on Identification Flowering Chinese Cabbage Varieties by ISSR Molecular Markers
Bibliographic record
Abstract
The study aimed to set up the ISSR reaction system of the flowering Chinese Cabbage,including the genomic DNA extraction,amplification,cycle time,primers screening.The results showed that the optimum temperature of a eggplant amplification was 48.0℃,and the best cycle time was 45cycle.4 primers were screened out from 49 ISSR primers totally to amplify the flowering Chinese Cabbage genome DNAs of 6 materials effectively,and 32 sites were amplified out totally,including 22 polymorphism sites with polymorphism rate of 68.80%.All of the 6 varieties could be differentiated from each other based on the fingerprints established by these specific bands.The Jaccard genetic similarity coefficients among flowering Chinese Cabbage vrieties were calculated by NTSYS-pc2.10e software.The genetic similarity coefficients among 6 flowering Chinese Cabbage varieties were between 0.19 and 0.77.The ISSR Markers showed that the higher genetic diversity of between materials.This study provided theoretical foundation to the seed purity identification and new varieties breeding of the chinese cabbage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".