Revisiting evolutionary dead ends in sockeye salmon (<i>Oncorhynchus nerka</i>) life history
Bibliographic record
Abstract
This study challenges recent hypotheses about sockeye salmon (Oncorhynchus nerka) colonization based on life history and broadens the pathways that investigators should consider when studying sockeye colonization of novel habitats. Most sockeye populations exhibit lake-type life histories. Riverine populations are thought to be more likely to stray from their natal stream to spawn and therefore colonize new habitat. We examined genetic relationships among five geographically proximate sockeye populations from the Aniakchak region of the Alaska Peninsula, Alaska. Specifically, we sought to determine if the genetic population structure was consistent with the hypothesis that a riverine population colonized a recently available upriver volcanic caldera lake, and whether recent volcanism led to genetic bottlenecks in these sockeye populations. Heterozygosity and allelic richness were not higher in the riverine population. Patterns of genetic divergence suggested that the geographically proximate riverine sockeye population did not colonize the lake; the caldera populations were more genetically divergent from the downstream riverine population (FST = 0.047) than a lake-type population in a different drainage (FST = 0.018). Our results did not suggest the presence of genetic bottlenecks in the caldera populations.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".