Barriers to gene flow in the lanceleaf stonecrop,?Sedum lanceolatum
Bibliographic record
Abstract
By David Stamper, Biological Sciences Advisor: Theresa Culley Presentation ID: PM_ATRIUM28 Abstract: The absence of gene flow provides chances for populations to become isolated, which can lead to speciation. In plants, gene flow can be restricted through barriers to pollinators and seed dispersal. One way to test these barriers is to look at natural populations that have been historically isolated such as lanceleaf stonecrop, Sedum lanceolatum Torr. (Crassulaceae). Previous work showed considerable genetic variation across a broad geographic scale in the S. lanceolatum. However, we were more interested in barriers at the local scale and how they can hinder gene flow. In this study, we assessed genetic variation at a small, local scale in S. lanceolatum along Jumpingpound Ridge in Alberta, Canada. We looked at two populations separated by the spine of a ridge and another population divided by encroaching forest. We tested the hypothesis that the spine of a ridge and the forest can act as barriers to gene flow, resulting in distinctive genetic variation within these respective populations. Sequence related amplified polymorphisms (SRAPs) were used to assess genetic variability within and among these populations. These markers allow us to discriminate individuals based on banding patterns that were scored using gel electrophoresis. Ultimately, scoring these bands allows us to assess the effectiveness of these natural features as barriers to gene flow. Understanding how these natural barriers impact gene flow may advance our knowledge of how human made barriers impact gene flow between populations.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".