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Record W2793172493 · doi:10.1139/cjfas-2017-0421

Does redistribution or local growth underpin rebuilding of Canada’s Northern cod?

2018· article· en· W2793172493 on OpenAlexaffvenueabout
George A. Rose, Sherrylynn Rowe

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsMemorial University of NewfoundlandUniversity of British Columbia
Fundersnot available
KeywordsFisheryGadusMetapopulationGeographyGroundfishStock (firearms)PopulationSpawn (biology)North seaOceanographyFishingEnvironmental scienceBiologyFisheries managementFish <Actinopterygii>Biological dispersalGeologyDemography

Abstract

fetched live from OpenAlex

The stock structure of Canada’s Northern cod (Gadus morhua), the largest of many depleted groundfish stocks having multiple spawning areas, is rebuilding by redistribution and not solely by local population growth. In 2007–2008, late winter acoustic surveys suggested initial rebuilding in the southern-most part of the offshore range (Bonavista Corridor, NAFO Divisions 3KL), likely including fish dispersing from the inshore. Thereafter, acoustically determined biomass increases averaged 30% per annum (to near 240 000 t in 2014). In contrast, formerly dominant stock areas farther north retained few fish, mostly juveniles. In 2015, however, biomass in the northern stock range (NAFO Division 2J) reached 65 000 t and mid-north Notre Dame Channel (3K) reached 101 000 t, with Bonavista Corridor declining to 136 000 t. Biomass pooled over all surveyed regions totaled 302 000 t, consistent with sustained 30% growth. Latitudinal gradients in cod size, age distributions, and individual growth existed both historically and recently, but not in 2015. The evidence suggests that the rapid increases of depopulated northern groups resulted from redistribution from the south within a metapopulation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.217

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.223
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations21
Published2018
Admission routes3
Has abstractyes

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