DEALING WITH DATA-POOR FISHERIES: A CASE STUDY OF THE BIG SKATE (RAJA BINOCULATA) IN BRITISH COLUMBIA'S GROUNDFISH FISHERY
Bibliographic record
Abstract
Groundfish fisheries target big skate (Raja binoculata) off the British Columbia coast. Catch comes mainly from Queen Charlotte Sound (QCS) and North Hecate Strait (NHS). Until now, sufficient data to evaluate stock status was not available. I parameterized a Graham-Schaefer model using catch (1996-2010), catch-per-unit-effort (1996-2010), and fishery-independent surveys (1984-2009) to estimate current abundance. QCS and NHS appear stable at their median estimated carrying capacities of 698,000 and 501,000 tonnes. Maximum sustainable yield (MSY) equalled 21,800 and 16,200 tonnes for QCS and NHS. Depletion-corrected average catch (DCAC) potential yield, a conservative estimate of MSY, equalled 17,500 and 13,000 tonnes for QCS and NHS. DCAC sustainable yield, total removals that may likely maintain a stock at current abundance, equalled 370 and 330 tonnes for QCS and NHS. To maintain current abundance, managers should monitor catches and keep them similar to historic catches since they do not appear to affect population dynamics.
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".