Wide‐Scale Population Sampling Identifies Three Phylogeographic Races of Basin Wildrye and Low‐Level Genetic Admixture with Creeping Wildrye
Bibliographic record
Abstract
ABSTRACT Basin wildrye [Leymus cinereus (Scribn. & Merr.) Á. Löve] and creeping wildrye [Leymus triticoides (Buckley) Pilg.] are outcrossing perennial grasses native to western North America. These divergent species are generally adapted to different habitats but can form fertile hybrids. Cultivars of both species are used in agriculture and conservation, but little is known about genetic diversity and gene flow among these species. Therefore, multilocus amplified fragment length polymorphism (AFLP) genotypes and chloroplast DNA sequences were evaluated from 536 L. cinereus and 43 L. triticoides plants from 224 locations of western United States and Canada. Bayesian‐cluster analysis detected three L. cinereus races corresponding to the Columbia, Rocky Mountain, and Great Basin regions. Possible admixture between species was detected in specific areas, but only 2.2% of the plants showed more than 10% introgression. The Columbia and Great Basin races were predominantly octoploid whereas most of the Rocky Mountain accessions were tetraploid. Approximately 36 and 7% of the AFLP variation was apportioned among species and races, respectively, but no discrete marker differences were detected among these groups. Although species can be distinguished using a relatively small set of AFLP markers showing divergent allele frequencies, at least 30 markers were needed to classify plants by race. Approximately 8 and 11% of the chloroplast DNA sequence variation was apportioned among species and races, but these markers were not practically useful for species or race identification.
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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) | 0.001 | 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".