Population structure and stock identification of sockeye salmon (<i>Oncorhynchus nerka</i>) in coastal lakes in British Columbia, Canada
Bibliographic record
Abstract
Population structure of sockeye salmon, Oncorhynchus nerka (Walbaum, 1792), from coastal lakes in British Columbia was determined from a survey of variation of 14 microsatellite loci, with approximately 6400 sockeye salmon analyzed from 40 populations. Populations from the Queen Charlotte Islands displayed fewer alleles per locus than did populations in other regions. Genetic differentiation among the populations surveyed was observed, with the mean FSTfor all loci being 0.077 (SD = 0.006). Differentiation among populations was approximately 13 times greater than annual variation within populations. Regional structuring of the populations surveyed was observed. The accuracy and precision of the estimated stock compositions generally increased as the number of observed alleles at the loci increased. Simulated mixed-stock samples generated from observed population frequencies in different regions suggested that variation at microsatellite loci provided reasonably accurate and precise estimates of stock composition for potential samples from marine or freshwater fisheries.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".