The Application of Rapid Microsatellite-Based Stock Identification to Management of a Chinook Salmon Troll Fishery off the Queen Charlotte Islands, British Columbia
Bibliographic record
Abstract
Abstract Since 1995, the Northern British Columbia (NBC) troll fishery has been managed to reduce exploitation on stocks of Chinook salmon Oncorhynchus tshawytscha from the West Coast of Vancouver Island (WCVI). Before 2002, management actions in the NBC troll fishery were generally large-scale quota reductions and area closures that resulted in substantially reduced catches of Chinook salmon relative to the existing quota. Since 2002, in-season microsatellite-based stock identification has been used to address WCVI Chinook salmon management in the NBC troll fishery. The change in management strategy has resulted in increased quota utilization and increased catches of approximately 390,000 fish during 2002–2005. The increased catch in the fishery was concurrent with average fishing mortality on the main WCVI hatchery indicator stock declining from an average 3.3% during the era of reduced catches (1995–2001) to 2.3% since 2002, when in-season, microsatellite-based stock identification was applied to guide the locations and timing of NBC troll fishery openings.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".