Estimating the Discard Mortality of Atlantic Cod in the Southern Gulf of Maine Commercial Lobster Fishery
Bibliographic record
Abstract
Abstract The Gulf of Maine (GOM) commercial lobster fishery has approximately 3.5 million actively fished traps and captures several nontargeted groundfish species, including Atlantic Cod Gadus morhua, as bycatch, yet there has been limited research on the incidental mortality of groundfish in this fishery. Although the mortality of Atlantic Cod has been estimated in other GOM commercial fisheries, unaccounted discard mortality in the lobster fishery may impair recovery efforts for this stock. To help meet research needs, we assessed the discard mortality rate of Atlantic Cod captured in the Maine Lobster Management Zone G commercial lobster fishery using acoustic transmitters and observations of viability. From 2016 to 2017, 111 Atlantic Cod were captured in 18,853 individual trap hauls and were observed for viability. A subsample of 54 Atlantic Cod was externally tagged with acoustic transmitters and observed after release. The combined at-vessel mortality (9.3%) and model-based long-term discard mortality (17.1%) estimates indicated an overall discard mortality rate of 24.8% for Atlantic Cod captured in commercial lobster gear. Based on this finding and the low bycatch of Atlantic Cod in the lobster fishery, the commercial lobster fishery may not be responsible—to the extent previously assumed—for hindering the GOM Atlantic Cod stock’s regrowth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".