Genetic Diversity of Walnut Revealed by AFLP and RAPD Markers
Bibliographic record
Abstract
AFLP and RAPD methods were used to investigate the genetic diversity of walnuts in western Sichuan plateau and Qinba mountainous regions. 35 samples were collected from 8 different regions, and 32 RAPD primers and 28 AFLP primer combinations were identified with polymorphism bands among the entire. 324 and 2155 fragments were respectively produced by RAPD and AFLP makers, and 86.1 % of RAPD bands and 57.2% of AFLP bands showed polymorphic with the size of 180~2000 bp and 50~1800 bp, respectively. The average amplified were 10.1 fragments per primer by RAPD and 76.9 fragments per pair primer by AFLP. The more polymorphic for genetic resource in Western Sichuan Plateau was observed by both RAPD and AFLP. The high number of alleles and the high expected genetic diversity detected with RAPD and AFLP markers indicate that western China has an important genetic diversity pool and abundant genetic variance of walnuts.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".