Micro-geographic population genetic structure within Arctic cod (Boreogadus saida) in Beaufort Sea of Alaska
Bibliographic record
Abstract
Abstract Many marine organisms show significant levels of genetic heterogeneity on local spatial scales despite exhibiting limited genetic structure at large geographic scales which can be produced through a variety of mechanisms. The Arctic cod (Boreogadus saida) is a circumpolar species and is a vital species in Arctic food webs. To examine population genetic structure of Arctic cod at macro- and micro-geographic scales, we characterized variation at mitochondrial DNA (mtDNA) and microsatellite loci among Arctic cod located in the Chukchi and Beaufort seas in Alaska. We found two distinct mtDNA haplotype clusters, although there was no underlying geographic pattern (FST = −0.001). Congruent with this finding, microsatellite loci suggested a panmictic population (FST = 0.001) across northern Alaskan marine waters at a large spatial scale. However, we found slight but significant micro-geographic partitioning of genetic variation in the southern shelf of the Beaufort Sea that appeared to be associated with the western reaches of the Mackenzie River plume. This fine-scale spatial pattern was not associated with kin-associated groups, suggesting larvae cohorts are not remaining together throughout development. We hypothesize that this pattern reflects the intermixing of Pacific and Arctic origin lineages of Arctic cod.
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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 | 0.001 | 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".