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Record W4407729160 · doi:10.1093/icesjms/fsaf015

Working with Northeastern United States lobster harvesters to develop acoustic trap retrieval in place of buoys and persistent vertical lines to reduce whale entanglements

2025· article· en· W4407729160 on OpenAlexaboutno aff
Eric Matzen, Regina Asmutis‐Silvia, Henry O. Milliken, Megan L Amico, Brian A Galvez, W. Brian Sharp, Mark F. Baumgartner, Michael J. Moore

Bibliographic record

VenueICES Journal of Marine Science · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric AdministrationTides FoundationPaul M. Angell Family FoundationJohns Hopkins UniversityWoods Hole Oceanographic InstitutionArthur L. and Elaine V. Johnson FoundationInternational Fund for Animal WelfareNew England BiolabsAnnenberg Foundation
KeywordsTrap (plumbing)WhaleOceanographyFisheryEnvironmental scienceGeologyGeographyMeteorologyBiology

Abstract

fetched live from OpenAlex

Abstract Vertical buoy lines (VBLs) between surface markers and bottom fishing gear frequently entangle large whales. These lethal and sublethal entanglements inhibit North Atlantic right whale (Eubalaena glacialis) recovery. Consequently, the use of persistent VBLs in situations of high entanglement risk off the east coasts of the USA and Canada is periodically prohibited. On demand, acoustic recovery systems make it possible to remove persistent VBLs, reducing entanglement risk, and potentially allowing fisheries to operate in such areas. To address concerns about performance, reliability, and safety, we evaluated numerous on-demand systems under normal fishing conditions. In 2020, conservationists, scientists, engineers, and lobster harvesters designed an experiment to trial on-demand systems in the New England offshore fisheries, using an open and honest dialogue while maintaining the confidentiality of data such as fishing locations. Between 2020 and 2023, 38 captains and their crews completed 5798 hauls using 431 on-demand units representing 10 different prototypes from multiple manufacturers. The geographic area expanded from limited offshore areas in 2020 to inshore, nearshore, and offshore waters in four different lobster management areas in 2022 and 2023. Trawl lengths ranged from 1 to 100 traps per trawl. Recovery success increased from 64% to 90% of hauls through the trials, although challenges remain, especially when fishing in deep waters or high current and tide locales. A parallel study is underway in Canada. The ability to ensure sustainable fisheries while significantly reducing entanglement risk is becoming a reality, with snow crabs and lobsters being sold in Canada and lobsters and Jonah crabs in the USA that were caught using experimental fishing permits and on-demand systems primarily in areas where persistent VBLs are seasonally prohibited for whale conservation.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.002

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 head0.024
GPT teacher head0.264
Teacher spread0.240 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

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