Pacific Salmon: Ecology and Management of Western Alaska’s Populations
Bibliographic record
Abstract
Abstract.—The sport fisheries for Chinook Oncorhynchus tshawytscha and coho salmon O. kisutch are a small but important component of fisheries in the Arctic-Yukon-Kuskokwim region (AYK). In the United States’ portion of the Yukon River drainage and in the Kuskokwim River drainage, only 5% of the total harvest (sport, commercial, subsistence) of these species are taken by the sport fisheries. In Norton Sound, sport fisheries harvest is somewhat more important and approximates 10% of the total Chinook and coho salmon harvest. The goal of sport fishery management is to maintain reliable fishing opportunities. In contrast, commercial and subsistence fishery management seeks a maximum sustainable harvest via efficient capture methods to provide for subsistence needs and viable commercial markets. The Alaska Board of Fisheries and Alaska Department of Fish and Game have primary responsibility for managing fisheries. Sport fishery management for salmon in the AYK region has little effect on annual spawning escapements of salmon due to low levels of harvest. Sport fishing gear is inherently inefficient and catch rates are variable. Bag limits are low in number and the focus of many anglers is on catching and releasing salmon, not on harvest. In recent years, catch-and-release fishing has increased and the proportion of salmon harvested from the total sport catch has declined. Catch-and-release fishing has been controversial with some local residents. Sport fisheries often occur upstream of, and after, the subsistence and commercial fisheries have completed their harvests. Maintaining reliable fishing opportunities are particularly critical to the few, small volume, AYK sport fish guide businesses. Clients generally arrange to fish several months before the start of the season. This small industry adds diversity in economic opportunities in rural Alaska. An inseason closure of the sport fishery for salmon can have a devastating economic impact on these small businesses.
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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) | 0.001 | 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".