Bycatch of Loons Assessed in Coastal Arctic Char Fisheries in the Canadian Arctic
Bibliographic record
Abstract
Abstract Bycatch in fisheries remains one of the biggest conservation threats to seabirds globally, but there has been limited attention given to bycatch in the Arctic. Here, we worked with Inuit commercial fishers in the Cambridge Bay region of Nunavut to record bycatch of birds as part of a fish bycatch reporting initiative, in weir and gill-net fisheries that target anadromous Arctic Char Salvelinus alpinus. Weir fisheries, and one of the gill-net fisheries (executed in freshwater), had no bird bycatch, but 291 loons (family Gavidae) were captured over 5 years in one estuarine–marine fishery, yielding an exceptionally high bycatch rate of 15.7 birds/1,000 net-meter-days. One of the species caught, the yellow-billed loon Gavia adamsii, is considered near threatened, but data on the population status of this species is insufficient to determine whether bycatch forms a significant threat. Nonetheless, deterrence efforts or other conservation options are needed in estuarine gill-net fisheries to reduce bird 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".