Pacific Salmon: Ecology and Management of Western Alaska’s Populations
Bibliographic record
Abstract
Abstract.—Chinook Oncorhynchus tshawytscha and chum O. keta salmon bycatch in the Bering Sea Aleutian Islands (BSAI) walleye pollock Theragra chalcogramma fishery has increased dramatically in recent years, reaching near record highs for both salmon species. This bycatch must either be thrown back into the water or saved for donation to food banks. Many of these salmon were bound for spawning streams in the Arctic-Yukon-Kuskokwim (AYK) region of western Alaska, where the people of the AYK region await the salmon’s return to provide for subsistence and commercial fisheries, and to fulfil a vital cultural role. To examine the interplay between the pollock fishery and western Alaska salmon stocks, this paper reviews important characteristics of the pollock fishery, western Alaska salmon stock status and origins of salmon bycatch in the pollock fishery, legal requirements to reduce bycatch, past and present bycatch management measures, and discusses possibilities for change and improvement to ensure that salmon bycatch and the impacts to western Alaska salmon are reduced. Current management under the voluntary rolling hot spot system provides an adaptive approach to bycatch management, but has not reduced salmon bycatch overall. To be effective, this system needs to be combined with a total cap on salmon bycatch. Technical approaches to reduce salmon bycatch, such as salmon excluder devices, should be developed and implemented. Social devices such as labelling regimes for sustainably caught fish could also play a role in reducing salmon bycatch.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".