Population integrity and connectivity in Northwest Atlantic herring: a review of assumptions and evidence
Bibliographic record
Abstract
Abstract Stephenson, R. L., Melvin, G. D., and Power, M. J. 2009. Population integrity and connectivity in Northwest Atlantic herring: a review of assumptions and evidence. – ICES Journal of Marine Science, 66: 1733–1739. The issue of herring population structure has been debated for more than a century. Population integrity and connectivity have become an increasingly important problem for both resource evaluation (e.g. concern for the use of appropriate modelling approaches) and management (e.g. increasing attention to the preservation of within-species diversity and the complexity of mixed-stock fisheries). In recent decades, there has been considerable advancement in the scientific information related to herring population structure, but papers continue to demonstrate a spectrum of conclusions related to population integrity and connectivity at various scales. We review herring stock structure in the western Atlantic, specifically addressing the assumptions currently being used in management and the validity of scientific evidence on which these assumptions are based. Herring of the western Atlantic exhibit considerable population discreteness and limited connectivity on the temporal and spatial scales that are of relevance to management. Maintaining the resulting population complexity is a challenge, particularly because preservation of within-species diversity is an important element of an ecosystem approach to management.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".