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Record W4392544645 · doi:10.1126/science.ade9121

Fishing for oil and meat drives irreversible defaunation of deepwater sharks and rays

2024· article· en· W4392544645 on OpenAlexaff
Brittany Finucci, Nathan Pacoureau, Cassandra L. Rigby, Jay H. Matsushiba, Nina Faure-Beaulieu, C. Samantha Sherman, Wade J. VanderWright, Rima W. Jabado, Patrícia Charvet, Paola A. Mejía‐Falla, Andrés F. Navia, Danielle H. Derrick, Peter M. Kyne, Riley A. Pollom, Rachel H.L. Walls, Katelyn B. Herman, K. K. Bineesh, Charles Cotton, J. M. Cuevas, Ross K. Daley, David A. Ebert, Daniel Fernando, Stela M. C. Fernando, Malcolm P. Francis, Charlie Huveneers, Hajime Ishihara, David W. Kulka, R. W. Leslie, Francis Neat, А. М. Орлов, Getulio Rincón, Glenn Sant, Igor V. Volvenko, Terence I. Walker, Colin A. Simpfendorfer, Nicholas K. Dulvy

Bibliographic record

VenueScience · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsFisheries and Oceans CanadaSimon Fraser University
Fundersnot available
KeywordsDefaunationThreatened speciesOverexploitationOverfishingFisheryFishingBycatchPopulationBiodiversityEcologyBiologyHabitat

Abstract

fetched live from OpenAlex

The deep ocean is the last natural biodiversity refuge from the reach of human activities. Deepwater sharks and rays are among the most sensitive marine vertebrates to overexploitation. One-third of threatened deepwater sharks are targeted, and half the species targeted for the international liver-oil trade are threatened with extinction. Steep population declines cannot be easily reversed owing to long generation lengths, low recovery potentials, and the near absence of management. Depth and spatial limits to fishing activity could improve conservation when implemented alongside catch regulations, bycatch mitigation, and international trade regulation. Deepwater sharks and rays require immediate trade and fishing regulations to prevent irreversible defaunation and promote recovery of this threatened megafauna group.

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 score0.014
Threshold uncertainty score0.027

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.008
GPT teacher head0.236
Teacher spread0.228 · 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

Citations62
Published2024
Admission routes1
Has abstractyes

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