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Record W2283979485 · doi:10.1139/cjfas-2015-0423

The effects of grey seal predation and commercial fishing on the recovery of a depleted cod stock

2016· article· en· W2283979485 on OpenAlexvenueno aff
Robin Cook, Vanessa Trijoulet

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersScottish Funding Council
KeywordsGadusFishingPredationFisheryStock (firearms)PopulationFunctional responseAtlantic codBiologyEnvironmental scienceEcologyPredatorGeographyDemography

Abstract

fetched live from OpenAlex

Cod (Gadus morhua) are preyed upon by grey seals (Halichoerus grypus), and there is debate over the impact this has had on the decline of stocks and their prospects for recovery. We analysed a depleted stock to the West of Scotland and show that seal predation rate is consistent with a type II functional response. Forward projections of a model including the functional response under varying levels of fishing and seal population size suggest that stock recovery is possible under current conditions, but there is a modest probability that the stock will decline further in both the short and long term. The potential recovery is fragile and sensitive to relatively small increases in either fishing or seal predation. Forward projection models that exclude the functional response estimate a lower probability of stock decline and may underestimate the risk to the stock. At low stock sizes and high fishing mortality rates, functional response models project slower recovery but the opposite is true at low fishing mortality.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.959
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.020
GPT teacher head0.210
Teacher spread0.191 · 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

Citations23
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicMarine animal studies overview→French-language works237,207→