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Using global catch data for inferences on the world’s marine fisheries

2012· article· en· W2152387152 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFish and Fisheries · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of British Columbia
FundersUniversity of British ColumbiaDeutsche Forschungsgemeinschaft
KeywordsMarine fisheriesFisheryStock (firearms)Stock assessmentFisheries managementAgricultureBusinessNatural resource economicsGeographyEconomicsFishingBiology

Abstract

fetched live from OpenAlex

Abstract Detailed stock assessments, including the estimation of the absolute biomass of the ‘stocks’ exploited by fisheries, are often viewed as the gold standard for indicators of their status. However, such stock assessments are not available for the overwhelming majority of exploited stocks and fisheries globally. This requires the development, testing and dissemination of other, less data‐demanding indicators for use throughout the world, for example, for comparing the status of fisheries between different maritime countries or large marine ecosystems. Stock status plots, initially developed by staff of the United Nations Food and Agriculture Organization to assess global fisheries, are reviewed here, and their most recent incarnation, which accounts for stock rebuilding, is found to provide a robust overview of fisheries and of the major trends besetting them.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.634
Threshold uncertainty score0.991

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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 head0.120
GPT teacher head0.316
Teacher spread0.196 · 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