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Comparing productivity of North Atlantic cod (<i>Gadus morhua</i>) stocks and limits to growth production

2003· article· en· W2078038992 on OpenAlexaff
Jean‐Denis Dutil, Keith Brander

Bibliographic record

VenueFisheries Oceanography · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans Canada
FundersEli Lilly and Company
KeywordsGadusAtlantic codFisherySalinityEnvironmental scienceOceanographyStock (firearms)Sea surface temperatureGrowth rateFish stockCatch per unit effortHaddockProductivityAnimal scienceBiologyGeographyFish <Actinopterygii>MathematicsGeologyEconomics

Abstract

fetched live from OpenAlex

Abstract Data from stock assessments were used to compare stock biomass, annual growth (Gs) and surplus production per capita (TSPc) and per unit biomass (TSPb) among 15 cod ( Gadus morhua ) stocks in the North Atlantic. TSPc ranged from 99 to 1012 g per fish among stocks and averaged 448 g per fish. TSPb ranged from 140 to 469 g kg −1 among stocks and averaged 294 g kg −1 . Gs varied considerably with low growth production associated with low surplus production. On average, cod produced 724 g per fish in growth annually with cod in the least productive stock producing 7.2 times less than in the most productive stock. The stocks divided into four clusters reflecting four levels of production. Celtic Sea, Irish Sea and West Scotland cod showed the highest levels of production whereas Eastern Scotian Shelf, Northeast Arctic, Northern Grand Bank, Northern and Southern Gulf of St Lawrence showed the lowest levels. Surface and bottom salinity and temperature differed significantly among clusters in a canonical discriminant analysis. Temperature and salinity correlated with the first and second canonical variates, respectively. The most productive stocks were associated with higher bottom salinity and temperature. None of the stocks, including stocks with a fast growth rate and living at higher temperatures, had a specific growth rate (SGR) close to the maximum rate observed in laboratory experiments. The difference between observed and maximum SGR decreased at temperatures above 6°C. Very cold temperatures resulted in smaller cod also achieving SGR values closer to the maximum. Temperature is a major determinant of stock production.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.027
Threshold uncertainty score0.773

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.212
Teacher spread0.193 · 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
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

Citations112
Published2003
Admission routes1
Has abstractyes

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