Genetic variation patterns of American chestnut populations at EST-SSRs
Bibliographic record
Abstract
The objective of this study is to analyze patterns of genetic variation at genic expressed sequence tag – simple sequence repeats (EST-SSRs) and at chloroplast DNA markers in populations of American chestnut (Castanea dentata Borkh.) to assist in conservation and breeding efforts. Allelic diversity at EST-SSRs decreased significantly from southwest to northeast along the Appalachian range, suggesting repeated founder events during postglacial migration. Comparatively high allelic diversity in Ontario, northwest of the Appalachian range, suggested more recent long-distance dispersal. Clinal variation of allele frequencies along the Appalachian axis was also in accordance with postglacial colonization from one refugium southwest of the Appalachian range. We observed clustering of the northwestern population from Ontario with southwestern populations and sharing of a rare chloroplast haplotype among western populations across the whole latitudinal range. This pattern is consistent with a divergence of postglacial migration routes and higher levels of more recent potentially human-mediated gene exchange between populations west of the Appalachian range. Population pairs east and west of the Appalachian axis showed pronounced allele frequency differences over a small geographic range. These patterns of genetic variation should be considered when sampling reproductive material for conservation and breeding.
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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 | 0.001 |
| 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) | 0.001 | 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".