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Record W4402749908 · doi:10.1038/s44183-024-00078-2

Rethinking sustainability of marine fisheries for a fast-changing planet

2024· article· en· W4402749908 on OpenAlex
Callum M. Roberts, Christophe Béné, Nathan Bennett, James S. Boon, William W. L. Cheung, Philippe Cury, Omar Defeo, Georgia de Jong Cleyndert, Rainer Froese, Didier Gascuel, Christopher D. Golden, Julie P. Hawkins, Alistair J. Hobday, Jennifer Jacquet, Paul S. Kemp, Mimi E. Lam, Frédéric Le Manach, Jessica J. Meeuwig, Fiorenza Micheli, Telmo Morato, Catrin Norris, Claire Nouvian, Daniel Pauly, Ellen K. Pikitch, Fabián Piña Amargós, Andrea Sáenz‐Arroyo, U. Rashid Sumaila, Louise Teh, Les Watling, Bethan C. O’Leary

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.

Bibliographic record

Venuenpj Ocean Sustainability · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
Fundersnot available
KeywordsSustainabilityBusinessResilience (materials science)Climate changeEnvironmental resource managementEnvironmental planningBiodiversityPsychological resilienceMarine biodiversitySustainable developmentPlanetFisheryNatural resource economicsEnvironmental economicsEnvironmental scienceEcologyEconomics

Abstract

fetched live from OpenAlex

Abstract Many seafood products marketed as “sustainable” are not. More exacting sustainability standards are needed to respond to a fast-changing world and support United Nations SDGs. Future fisheries must operate on principles that minimise impacts on marine life, adapt to climate change and allow regeneration of depleted biodiversity, while supporting and enhancing the health, wellbeing and resilience of people and communities. We set out 11 actions to achieve these goals.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.250
Teacher spread0.241 · 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