A state-space stock assessment model for American plaice on the Grand Bank of Newfoundland
Bibliographic record
Abstract
The current stock assessment model for American plaice (Hippoglossoides platessoides) on the Grand Bank of Newfoundland (NAFO Divisions 3LNO) is a virtual population analysis (VPA).This model does not account for the considerable uncertainty about the landings data for this stock.Retrospective patterns have also been noted in the current assessment with overestimation of spawning stock biomass (SSB) and underestimation of fishing mortality (F).Via a thorough model selection process, we develop a state-space stock assessment model (SSM) for this stock that accounts for the uncertainties in the landings data and reduces the retrospective patterns.Our SSM fit the data well, with overall trends in SSB and average F (ages 9-14) similar to those estimated from the current VPA.The retrospective patterns for the SSM were reduced for both SSB and average F which should lead to the provision of better scientific advice for the management of this stock.An important result from our analysis suggests that the current assumption for natural mortality (M) in the stock assessment model may be too low.The lack of recovery of the stock of American plaice on the Grand Bank has often been attributed to overfishing, however fixing M within the model to be lower than is reasonable may be over-estimating the relative impact of F and subsequently over-stating the contribution of fishing mortality to the lack of recovery of the stock. Spring
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".