Pacific Salmon: Ecology and Management of Western Alaska’s Populations
Bibliographic record
Abstract
Abstract.—The genetic population structures of chum Oncorhynchus keta, Chinook O. tshawytscha, coho O. kisutch, sockeye O. nerka, and pink O. gorbuscha salmon within the AYK region are described based on available published and unpublished information. The most detailed genetic data were for chum salmon where major groups included: (1) summer-run fish returning to coastal rivers and the lower reaches of the Yukon and Kuskokwim Rivers, (2) upper Yukon River, and (3) upper Kuskokwim River fall-run populations. AYK Chinook and coho salmon populations showed similar patterns of differentiation within the Yukon and Kuskokwim Rivers, although each species had quite different spatial separation and timing. Based on unpublished genetic data from AYK sockeye salmon populations, Norton Sound populations were grouped together and were distinct from ten other areas within the Yukon and Kuskokwim drainages which had affinities with Bristol Bay populations. Available pink salmon data were insufficient to estimate population structures. Similarity of AYK and Susitna River chum and Chinook salmon populations suggest a common ancestry that may reflect an historical connection of these drainages. Low species-wide indices of among-population genetic variation (FST) in chum and pink salmon suggest that regionally based conservation strategies for these species will be effective. In contrast, Chinook, coho, and sockeye salmon had higher FST values and require population-specific strategies. Genetic stock identification methods (mixed stock analysis) provided valuable estimates of oceanic distributions of AYK chum salmon, and in-season estimates of chum, Chinook, and coho salmon stocks migrating within the Yukon and Kuskokwim Rivers. The genetic information now known about salmon in the AYK region will help the formulation and design of future investigations, and will ultimately promote a better understanding, management, and conservation of AYK salmon.
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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 | 0.000 | 0.000 |
| 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".