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Record W2191447420 · doi:10.1111/mms.12292

Drag from fishing gear entangling North Atlantic right whales

2015· article· en· W2191447420 on OpenAlexfundno aff
Julie van der Hoop, Peter Corkeron, John Kenney, Scott Landry, David Morin, Jamison Smith, Michael J. Moore

Bibliographic record

VenueMarine Mammal Science · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaNational Oceanic and Atmospheric AdministrationCooperative Institute for the North Atlantic Region
KeywordsDragMarine engineeringRight whaleBuoyPopulationFishingWave dragDrag coefficientFisheryEnvironmental sciencePhysicsOceanographyGeologyMechanicsEngineeringWhaleBiologyDemography

Abstract

fetched live from OpenAlex

Abstract Lethal and sublethal fishing gear entanglement is pervasive in North Atlantic right whales ( Eubalaena glacialis ). Entanglement can lead to direct injury and is likely to incur substantial energetic costs. This study (1) evaluates drag characteristics of entangled right whales, (2) contextualizes gear drag measurements for individual whales, and (3) quantifies the benefits of partial disentanglement. A load cell measured drag forces on 15 sets of fishing gear removed from entangled right whales, a towed satellite telemetry buoy, and 200 m of polypropylene line as it was shortened to 25 m, as they were towed behind a vessel at ~0.77, 1.3, and 2.1 m/s (~1.5, 2.5, and 4 knots) and ~0, 3, and 6 m depth. Mean drag ranges from 8.5 N to 315 N, and can be predicted from the dry weight or length of the gear. Combining gear drag measurements with theoretical estimates of drag on whales' bodies suggests that on average, entanglement increases drag and propulsive power by 1.47 fold. Reducing trailing line length by 75% can reduce parasitic gear drag by 85%, reinforcing current disentanglement response practices. These drag measurements can be incorporated into disentanglement response, serious injury determination, and evaluation of sublethal effects on population dynamics.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.005
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.021
GPT teacher head0.226
Teacher spread0.205 · 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; both teacher heads agree on what is shown here.

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

Citations46
Published2015
Admission routes1
Has abstractyes

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