Population Genetics of Arctic Grayling Distributed Across Large, Unobstructed River Systems
Bibliographic record
Abstract
Abstract We investigated the population genetics of Arctic Grayling Thymallus arcticus distributed throughout several connected river systems in Alberta, Canada. Broad‐ and fine‐scale population structure was examined by genotyping nine microsatellite loci in 1,116 Arctic Grayling captured from 40 sites in the Hay, Peace, and Athabasca River basins. Genetic diversity tended to decline from north to south (allelic richness versus latitude: Spearman's rank correlation rs = 0.793, P < 0.05); the lowest level of diversity was detected in a stocked population. We found significant genetic divergence between and within major river basins (overall genetic differentiation index FST [θST] = 0.13) and strong isolation‐by‐distance patterns in the Peace River basin (Mantel's r = 0.97, P < 0.001) and Athabasca River basin (Mantel's r = 0.95, P < 0.001). Evidence for gene flow among sites in neighboring rivers (i.e., 25–100km apart) was common; significant genetic differentiation tended to occur at the subbasin level. The spatial scale of differentiation for Arctic Grayling is intermediate to those reported for other sympatric salmonid species that differ in population size and degree of spawning site fidelity.
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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 | 0.001 |
| 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".