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Record W2131140497 · doi:10.1093/icesjms/fsp189

Population integrity and connectivity in Northwest Atlantic herring: a review of assumptions and evidence

2009· review· en· W2131140497 on OpenAlexaff
Robert L. Stephenson, Gary D. Melvin, Michael Power

Bibliographic record

VenueICES Journal of Marine Science · 2009
Typereview
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsHerringPopulationGeographyStock (firearms)Atlantic herringFisheryFisheries managementFisheries scienceEcologyBiologyFish <Actinopterygii>FishingClupea

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.750
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.077
GPT teacher head0.377
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreReview

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".

Quick stats

Citations57
Published2009
Admission routes1
Has abstractyes

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