Assessing the Technical and Economic Viability of Galvanizing Snow Crab (Chionoecetes opilio) Traps
Why this work is in the frame
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Bibliographic record
Abstract
Commercial harvesting of snow crabs (Chionoecetes opilio) began in Newfoundland and Labrador, Canada, in 1967. Today, the fishery consists of 2188 active fishing licenses and has grown into the province’s most economically valuable fishery. Snow crabs are captured using conical traps consisting of a mild carbon steel frame, hard plastic entry funnel and a jacket of polyethylene netting. The frames of these traps corrode over time, which is expedited by being deployed in marine environments and stored on land near the ocean when not in use. As a result, there is interest within the community to increase the longevity of crab traps. One solution is to galvanize the steel frames prior to installing the funnel and netting. However, before harvesters transition to galvanized traps, two questions must be answered. Will the use of galvanized steel negatively impact catch rates? Will the life cycle of a crab trap be extended sufficiently to justify the additional cost of galvanizing? This study employed a generalized linear mixed model to evaluate the catch of legal-sized male crabs (CPUE) during the commercial fishery as a function of three trap frame treatments (old traditional, new traditional and new galvanized). We also assessed the economic viability of galvanizing trap frames by evaluating the life cycle cost (LCC) of traditional and galvanized traps to the harvester. The LCC was calculated over a range of inflation (0–6%) and discount (3–20%) rates. Our results found no significant difference in CPUE between new traps (traditional vs. galvanized) and concluded that except during instances of very high discount rates (12.9–19.9%), it is economically favourable to galvanize crab trap frames.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it