Testing Square Mesh Panels In Trap Nets To Reduce The Catch Of Juvenile Atlantic Cod
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.Thousands of traps averaging 100 meters on the rounds and 18 meters deep are operated around Newfoundland annually to catch Atlantic Cod. The catch of Cod in those traps often exceeds the small fish protocol of not more than 15% under 43 cm. In the past this has resulted in the closure of the Cod trap fishery in some areas. In 1997 traps operated in nine different locations on the West Coast of Newfoundland were modified with square mesh panels to reduce the catch of small fish. All square mesh panels measured six meters by six meters and were installed into the trap drying twine. Five of the panels were 102-mm mesh, and the other four were 117-mm mesh. Each trap had retainer bags attached to the square mesh panels to capture the escaping fish. Mesh sizes in the retainer bags varied from 57-mm to 102-mm. The nine traps were hauled up to two times each day during the June-July, traditional trap season. Samples of 250 fish were collected from each trap and retainer for each set, and the length measured. During the testing period, 40,200 kilograms of Cod were caught in 56 trap hauls. Cumulative length frequency graphs were generated for each trap and retainer showing the commutative percentage of fish caught at various fish lengths. The percentage of fish <43 cm. In three of the four traps with 117-mm square mesh panels was <15%, while only one of the traps with 102- mm square mesh panels had <15% small fish.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".