Population genetic structure of Bryde’s whales (<i>Balaenoptera brydei</i>) on the central and western North Pacific feeding grounds
Bibliographic record
Abstract
The genetic structure of Bryde’s whale ( Balaenoptera brydei) on the central and western North Pacific feeding grounds was investigated using a total of 1195 mitochondrial control region sequences and 1182 microsatellite genotypes at 17 loci in specimens collected from three longitudinal areas, 1W (135°E–165°E), 1E (165°E–180°), and 2 (180°–155°W). Genetic diversities were similar among areas and a haplotype network did not show any geographic structure, while an analysis of molecular variance found evidence of genetic structure in this species. Pairwise FST and [Formula: see text] estimates and heterogeneity tests attributed this structure to weak but significant differentiation between areas 1W/1E and 2. A Mantel test and a high-resolution analysis of genetic diversity statistics showed a weak spatial cline of genetic differentiation. These findings could be reconciled by two possible stock structure scenarios: (1) a single population with kin-association affecting feeding ground preference and (2) two populations with feeding ground preference for either area 1W or area 2. An estimated dispersal rate between areas 1W and 2 indicates that both scenarios should be considered as a precautionary principle in stock assessments.
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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 | 0.001 |
| 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".