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Record W4312190904 · doi:10.1139/cjfas-2022-0190

Escape, discard, and landing probability of <i>Nephrops norvegicus</i> in the Mediterranean Sea creel fishery

2022· article· en· W4312190904 on OpenAlexvenueno aff
Marina Mašanović, Bent Herrmann, Jure Brčić

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Ecology and Invasive Species
Canadian institutionsnot available
Fundersnot available
KeywordsNephrops norvegicusFisheryMediterranean seaMediterranean climateFishingBiologyEnvironmental scienceEcologyCrustaceanDecapoda

Abstract

fetched live from OpenAlex

Size selection in creel fishery consists of two processes: the first taking place in the creel on the seabed and the second made by the fisher on the vessel. However, no study has ever considered both processes when assessing the size selection in creel fisheries. This study presents a framework for including both and demonstrates it to predict the effect of mesh size and shape on the creel fishery targeting the Norway lobster ( Nephrops norvegicus) in the Mediterranean Sea. For this specific fishery, we demonstrate that both processes play a role in the overall size selection. Furthermore, we predict an optimal creel mesh size, which potentially eliminates the second process taking place on the vessel, while maintaining high efficiency for the first process on the seabed for the targeted sizes of Nephrops. The approach here presented can be also applied to other creel fisheries.

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)0.001
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 score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

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

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 head0.023
GPT teacher head0.203
Teacher spread0.180 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicMarine Ecology and Invasive SpeciesFrench-language works237,207