Population genetics and phylogeography of the blue rockfish (<i>Sebastes mystinus</i>) from Washington to California
Bibliographic record
Abstract
Blue rockfish (Sebastes mystinus) are a major component of nearshore ecology and fisheries on the west coast of the United States, but the extent of spatial structuring between localized populations is unknown. I sampled 245 blue rockfish at eight locations from Washington to California and sequenced a 498 base pair portion of the mitochondrial DNA control region to describe genetic diversity, population structure, and phylogeography. Haplotype diversity was high, but nucleotide diversity was low, indicating historically unstable population dynamics. Significantly high levels of population differentiation were detected among sample sites (maximum pairwise FST: full sequence = 0.25, reduced sequence = 0.74, P < 0.001), with a distinct break (ΦCT: full sequence = 0.12; reduced sequence = 0.36, P < 0.05) north and south of Cape Mendocino and no overall trend between geographic and genetic distances. Cape Mendocino may prove an important biogeographic barrier to other marine organisms, but it has not been extensively explored as such. The northern subpopulation derived from the southern subpopulation, but little contact has been made between the populations for potentially thousands of years. Therefore, repopulation of a depleted southern subpopulation is unlikely to come from the less-fished northern subpopulation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".