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Record W2270985316 · doi:10.1139/cjfas-2015-0096

Assessing natural mortality of Bay of Biscay anchovy from survey population and biomass estimates

2016· article· en· W2270985316 on OpenAlexvenueno aff
Andrés Uriarte, Leire Ibaibarriaga, Lionel Pawlowski, Jacques Massé, Pierre Petitgas, María Santos, Dankert W. Skagen

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsEngraulisAnchovyBayStock assessmentFisheryPopulationBiomass (ecology)Stock (firearms)GeographyBiologyEcologyOceanographyEnvironmental scienceFishingDemographyFish <Actinopterygii>Geology

Abstract

fetched live from OpenAlex

The closure of the anchovy (Engraulis encrasicolus) fishery in the Bay of Biscay between 2005 and 2010 because of low biomass levels provided an opportunity to estimate natural mortality using data from egg (daily egg production method, DEPM) and acoustic surveys implemented for the assessment of this population since 1987. Assuming that natural mortality (M) is constant over time and that catchability in both surveys is equal for all ages, M could be estimated using log-linear models on the series of surveys of population numbers at age and seasonal integrated stock assessments. The analysis suggests M values of around 0.9 for a common natural mortality at all ages. However, we found firm evidence that natural mortality at ages 2 and older (M2+) is markedly higher than at age 1 (M1), which indicates senescent mortality, a possibility suggested a long time ago for this type of short-lived species.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.290
Teacher spread0.244 · 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

Citations18
Published2016
Admission routes1
Has abstractyes

Explore more

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