Genetic diversity of bluebunch wheatgrass (<i>Pseudoroegneria spicata</i>) in the Thompson River valley of British Columbia
Bibliographic record
Abstract
Bluebunch wheatgrass ( Pseudoroegneria spicata (Pursh) A. Löve) is a cool-season perennial grass native to semi-arid regions of western North America and has been used for habitat restoration. However, the genetic diversity of this species is poorly understood. A total of 172 expressed sequence tag-derived simple sequence repeat (eSSR) primer pairs that had been developed for wheat were characterized for genetic diversity studies of bluebunch wheatgrass. Of these, 12 eSSR primer pairs were found to be informative and were applied to screen 216 plants collected from six locations with two different elevations in the Thompson River valley of British Columbia. These analyses revealed a total of 106 eSSR polymorphic alleles (or bands) scorable for each sample. The number of polymorphic bands per primer pair ranged from 2 to 17 with a mean of 8.8. The frequencies of these bands ranged from 0.005 to 0.995 and averaged 0.146. Most (92.6%) of the eSSR variation detected was present within the 12 populations assessed. The between-population eSSR variability was significantly associated with their geographic distances, but not with their elevations. These findings are useful for genetic diversity and genetic mapping studies of this grass species and should facilitate the sampling and development of bluebunch wheatgrass germplasm for germplasm conservation and habitat restoration.
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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 | 0.001 | 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) | 0.001 | 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".