MétaCan
Menu
Back to cohort
Record W2923299160 · doi:10.3989/scimar.04837.18a

Reconstruction of marine small-scale fisheries captures in the Canary Islands (NE Atlantic Ocean) from 1950 to 2010

2019· article· en· W2923299160 on OpenAlexaff
J.J. Castro, Esther Divovich, Alicia Delgado de Molina Acevedo, Antonio Barrera-Luján, Rodrigo Riera

Bibliographic record

VenueScientia Marina · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsUniversity of British Columbia
FundersUniversidad de Las Palmas de Gran CanariaPew Charitable Trusts
KeywordsDemersal zoneFisheryDiscardsFishingGeographyExclusive economic zoneMarine fisheriesSubsistence agricultureRecreational fishingScale (ratio)OceanographyBiologyCartographyAgricultureGeology

Abstract

fetched live from OpenAlex

Total marine fisheries catches within the exclusive economic zone of the Canary Islands, Spain, were reconstructed to include catches from the various small-scale artisanal fleets and their discards, as well as subsistence, recreational and other unreported catch. Total reconstructed catch was estimated at 38600 t in 1950, increasing to 81200 t in 1985, declining to approximately 43700 t year–1 in the early 2000s, and finally spiking to about 65300 t year–1 by the late 2000s. These catches coincide with a severe depletion of fish stocks, especially those of demersal species, due in part to fishing overcapacity in the artisanal sector, despite attempts to limit effort by the government. Spain only started to report catches to the FAO in 2006, and from 2006 to 2010 reconstructed catch was seven times the reported catch. Nearly 70% of this catch was from the recreational fishing sector, due in part to technological advancements and increased investments in the construction and improvement of secondary ports.

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 categoriesInsufficient payload (model declined to judge)
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 score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.175
Teacher spread0.168 · 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.

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

Citations19
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueScientia MarinaSame topicCoral and Marine Ecosystems StudiesFrench-language works237,207