Hauling Snow Crab Traps in Eastern Canada: A Study Documenting Tension in Ropes
Bibliographic record
Abstract
Entanglement in commercial fishing gear is one of the main factors inhibiting the recovery of critically endangered North Atlantic right whales. Installing low-breaking-strength (LBS) components in the buoy lines and main lines of stationary fishing gear may be a viable solution for some fisheries. But is it an effective solution for deep-water trap fisheries? This study quantified in-line rope tensions observed during fishing operations for snow crab (Chionoecetes opilio) in Newfoundland and Labrador, Canada. We conducted a controlled fishing experiment in which we documented the loads experienced while hauling fleets of traps. The results showed that several factors contributed to the loads observed, including the components of the traps, the presence of crabs, and environmental conditions such as wind direction and wave height. According to the statistical models, the maximum tension from the estimated marginal means was 477.53 kgf in the buoy line and 987.99 kgf in the main line for the baited hauls, which exceeds the safe working load (154 kgf) of the proposed low-breaking-strength components. Our results suggest that LBS components are not a viable solution for this deep-water fishery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".