MétaCan
Menu
Back to cohort
Record W3211709679 · doi:10.1111/jfb.14942

Decline in <scp>Atlantic</scp> wolffish <i>Anarhichas lupus</i> in the <scp>North Sea</scp>: Impacts of fishing pressure and climate change

2021· review· en· W3211709679 on OpenAlexaff
Joanna K. Bluemel, Simon H. Fischer, David W. Kulka, Christopher P. Lynam, Jim R. Ellis

Bibliographic record

VenueJournal of Fish Biology · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans Canada
FundersDepartment for Environment, Food and Rural Affairs, UK Government
KeywordsFishingBycatchDemersal zoneFisheryBiologySystemic lupus erythematosusOverexploitationClimate changeEcologyPopulationRange (aeronautics)OverfishingOceanography

Abstract

fetched live from OpenAlex

Anarhichas lupus is a boreo-Arctic species with biological characteristics often associated with vulnerability to overexploitation. Although not commercially targeted in the North Sea, A. lupus is a bycatch species in mixed demersal fisheries. Here we provide an overview of the status of A. lupus in the North Sea, as observed from commercial landings and fishery-independent trawl survey data. A. lupus was once common across much of the central and northern North Sea but, since the 1980s, have declined in abundance, demographic characteristics (reduced size) and geographical range, with the shallower and more southerly parts of its range most impacted. A. lupus is still relatively frequent in the northern North Sea, where fishing intensity, though decreasing, is high. Bycatch through fishing remains a potential threat and, considering the likely impacts of predicted climate change on cold-water species, risks of further regional depletion and/or range contraction remain. Whether or not A. lupus is able to re-establish viable populations in former habitat in UK coastal waters is unknown. Given the lack of data, the precautionary principle would suggest that manageable pressures be minimized where the species and its habitat are at risk of further impacts, and more regular assessments of population status be undertaken.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.070

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)0.0020.000

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 head0.044
GPT teacher head0.312
Teacher spread0.268 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations15
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Fish BiologySame topicMarine and fisheries researchFrench-language works237,207