Early life-stage and adult productivity dynamics derived from a state-space stock assessment model for data-limited Thorny Skates (Amblyraja radiata Donovan, 1808) in NAFO Divisions 3LNO and Subdivision 3Ps
Bibliographic record
Abstract
Thorny skate fisheries in the Northwest Atlantic are of heightened management interest because of the vulnerability of the species to fishing and their severe declines in the Gulf of St. Lawrence down to the Gulf of Maine. North of these regions in NAFO Divisions 3LNO and Subdivision 3Ps, thorny skate are the most abundant skate species and there has been directed fishing for this stock since the 1980’s. However, there is no stock assessment model to evaluate the impacts of fishery catches or to provide future catch advice to fisheries managers. We present a state-space stock assessment model which integrates length-based survey indices and total fishery catch information to estimate population dynamics, including changes in natural mortality rates. However, this is a data limited stock so our assessment model makes simplifying assumptions which we test with sensitivity analyses. We also conduct simulation analyses of the model. These results indicate that the model estimates are robust to assumptions and reliable in simulations, although we found some bias which should be acknowledged and better understood if the model is used for management advice. Our model indicates that the stock declined rapidly between 1986 and 1995 but increased since then and in 2019 the SSB was about half of the average value in 1984–1986 prior to the decline.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".