Mitochondrial population structure and post‐glacial dispersal of longnose sucker <i>Catostomus catostomus</i> in Labrador, Canada: evidence for multiple refugial origins and limited ongoing gene flow
Bibliographic record
Abstract
Two hundred and eighty-seven longnose sucker Catostomus catostomus were collected from 14 lakes in Labrador, 52 from three lakes in Ontario, 43 from two lakes in British Columbia and 32 from a lake in Yukon; a total of 414 in all. The resulting 34 haplotypes (20 in Labrador) contained moderate haplotypic diversity (h = 0·657) and relatively low nucleotide diversity (π = 3·730 × 10(-3) . Mean ϕST (0·453, P < 0·05) over all populations revealed distinct genetic structuring among C. catostomus populations across Canada, based on province, which was validated by the analysis and spatial analysis of molecular variance (c. 80% variation between provinces). These results probably reflect the historical imprint of recolonization from different refugia and possibly indicate limited ongoing gene flow within provinces. A haplotype network revealed one major and two minor clades within Labrador that were assigned to the Atlantic, Beringian and Mississippian refugia, respectively, with tests of neutrality and mismatch distribution indicative of a recent population expansion in Labrador, dated between c. 3500 and 8300 years ago.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".