An evaluation of gray whale (Eschrichtius robustus) mortality incidental to fishing operations in British Columbia, Canada
Bibliographic record
Abstract
Gray whale (Eschrichtius robustus) mortality incidental to commercial fishing operations in British Columbia (BC), Canada was evaluated by two methods: a mailed questionnaire survey of all commercial fishing licence holders in the province; and a review of records of incidental catches, strandings and dead floating animals from published and unpublished sources. Of 5,375 surveys sent out, 848 were returned of which 729 could be used (15.8%). Forty-two incidents with gray whales were reported, including three mortalities. From sources other than the questionnaire for the period up to 1989, 41 records of stranded and dead floating gray whales were obtained, of which four were judged to have been killed incidentally in fishing operations. Twenty-six of these animals had not been examined closely, but extrapolation from the 15 detailed records suggests that 27% of the dead gray whales reported in BC die incidentally in fisheries. Collisions with fishing gear are estimated to occur approximately 20 times per year. Mortality occurs in salmon drift gillnet, salmon seine, longline and trap fisheries. There is also one record of an individual entangled and drowned in a herring net pen, as well as an individual entangled in a herring set gillnet. Estimates of annual mortality are approximately two individuals using data obtained from the questionnaire and 2.4 individuals using stranding data. Biases are present for both sampling methods, but the estimated mortality levels are small relative to population size. Subsequent records (n = 40) for the period 1990–95 were also examined for comparison.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".