Biological reference points for sea scallops (<i>Placopecten magellanicus</i>): the benefits and costs of being nearly sessile
Bibliographic record
Abstract
In this paper, we concentrate on spatial aspects of growth and reproduction for sea scallops (Placopecten magellanicus) to advance the general theory for development of reference points for sessile animals and to illustrate the general points with several specific examples. Nonlinear mixed effects models can be used to define the spatial distribution of growth rates and their implications for the definition of growth overfishing. We develop a basin model to illustrate that the typical "boom and bust" effects, often attributed to environmental factors, are explained equally well by spatial variations in habitat quality, spatial concentration of fisheries, and dispersal of larvae among areas. Results suggest that incentives to concentrate fishing effort in lower productivity areas may be an effective tool for reducing recruitment variation and improving yields. Reductions in fishing mortality might be possible with closed areas as they can be used to reduce the concentration of effort on high scallop densities. Further, rotational area management strategies can offer the promise of balancing demands for increased yield, prevention of recruitment overfishing, maintaining spawning reserves, and reducing habitat damage and bycatch.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".