An Overview of RAPD Analysis to Estimate Genetic Relationships in Lowbush Blueberry
Bibliographic record
Abstract
SUMMARY Randomly amplified polymorphic DNA (RAPD) analysis, a simple dominant molecular marker technique, has been used extensively for cultivar identification and relatedness studies in many perennial woody species. Thus, this technique should provide genetic information for lowbush blueberry (Vaccinium angustifolium Ait.). Young leaves of lowbush blueberry from field clones with varying phenotype were collected for DNA extraction. Pre-screening of RAPD primers resulted in 11 polymorphic primers and 140 consistent RAPD fragments. Eight primers were selected as useful for our study, the fragments scored and the data analyzed with Genstat5 to calculate similarity, produce dendrograms and perform a principal coordinate analysis. The RAPD analysis was able to identify distinct field clones. Average genetic similarity among field clones was 68% reflecting expected genetic variation. Approximately 15% of the field clones were not related. RAPD analysis is a useful tool for genetic relationship studies in lowbush blueberry and may provide similarity information for future pollination/productivity research.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".