Genetic diversity of arctic bramble (<i>Rubus arcticus</i>L. subsp.<i>arcticus</i>) as measured by amplified fragment length polymorphism
Bibliographic record
Abstract
The levels of genotypic and genetic variation were estimated in six natural populations of arctic bramble (Rubus arcticus L. subsp. arcticus) in Finland. Using three primer combinations, a total of 117 amplified fragment length polymorphisms (AFLP) were found. The results were highly reproducible and allowed identification of 78 genets among the 122 plants of arctic bramble studied. Genotypic variation measured as Simpson index (D) was high in all populations, ranging from 0.72 to 0.94. Also, the level of genetic variation measured as Shannon index was relatively high in all populations, ranging from 0.19 to 0.32 (average 0.26). The high levels of genetic diversity indicate that sexual reproduction has played a significant role in these populations. The hierarchical analysis of molecular variance (AMOVA) partitioned 48% of the genetic variation among populations, suggesting a high level of population differentiation and a low level of interpopulation gene flow. Genetic diversity among ten currently grown cultivars of arctic bramble and hybrid arctic bramble (R. arcticus subsp. arcticus × R. arcticus subsp. stellatus) was large, and the subspecies were clearly distinguished from each other based on the AFLP marker data.Key words: AFLP, AMOVA, population, natural habitat, Rubus arcticus subsp. arcticus, Rubus arcticus subsp. stellatus.
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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 | 0.001 | 0.000 |
| 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".