Genetic stock composition analysis of the Chinook salmon bycatch from the 2015 Bering Sea walleye pollock (Gadus chalcogrammus) trawl fishery.
Bibliographic record
Abstract
A genetic analysis of samples from the Chinook salmon (Oncorhynchus tshawytscha) bycatch of the 2015 Bering Sea-Aleutian Island (BSAI) trawl fishery for walleye pollock (Gadus chalcogrammus) was undertaken to determine the overall stock composition of the bycatch. Samples were genotyped for 43 single nucleotide polymorphism (SNP) DNA markers and results were estimated using the Alaska Department of Fish and Game (ADF&G) SNP baseline. In 2015, genetic samples from the Bering Sea were collected using a systematic random sampling protocol where one out of every 10 Chinook salmon encountered was sampled. Based on the analysis of 1,757 Chinook salmon bycatch samples collected throughout the 2015 BSAI walleye pollock trawl fishery, Coastal Western Alaska stocks dominated the sample set (40%) with smaller contributions from British Columbia (22%), West Coast U.S. (WA/OR/CA) (15%), and North Alaska Peninsula (11%) stocks. Analysis of temporal groupings within the pollock "A" and "B" seasons revealed changes in stock composition during the course of the year with lower contributions of Coastal Western Alaska, North Alaska Peninsula, and Upper Yukon stocks and higher contributions of West Coast U.S. (WA/OR/CA), British Columbia, NW Gulf of Alaska, and Coastal Southeast Alaska stocks during the "B" season.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".