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Record W4296618079 · doi:10.1038/s42003-022-03959-9

Ultrasonic antifouling devices negatively impact Cuvier’s beaked whales near Guadalupe Island, México

2022· article· en· W4296618079 on OpenAlexaff
Jennifer S. Trickey, Gustavo Cárdenas‐Hinojosa, Lorenzo Rojas‐Bracho, Gregory S. Schorr, Brenda K. Rone, Eva Hidalgo‐Pla, Ally Rice, Simone Baumann‐Pickering

Bibliographic record

VenueCommunications Biology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsThe Arctic Eider Society
FundersOffice of Naval ResearchComisión Nacional de Áreas Naturales ProtegidasSecretaría de Medio Ambiente y Recursos NaturalesInternational Community FoundationMarisla FoundationPADI FoundationU.S. Department of Defense
KeywordsMarine lifeDisturbance (geology)Environmental scienceMarine ecosystemPopulationOceanographyWildlifeRange (aeronautics)FisheryBiofoulingGeographyEcosystemEcologyGeologyBiologyEngineering

Abstract

fetched live from OpenAlex

Widespread use of unregulated acoustic technologies in maritime industries raises concerns about effects on acoustically sensitive marine fauna worldwide. Anthropogenic noise can disrupt behavior and may cause short- to long-term disturbance with possible population-level consequences, particularly for animals with a limited geographic range. Ultrasonic antifouling devices are commercially available, installed globally on a variety of vessel types, and are marketed as an environmentally-friendly method for biofouling control. Here we show that they can be an acoustic disturbance to marine wildlife, as seasonal operation of these hull-mounted systems by tourist vessels in the marine protected area of Guadalupe Island, México resulted in the reduced presence of a potentially resident population of Cuvier's beaked whales (Ziphius cavirostris). Human activities are rapidly altering soundscapes on local and global scales, and these findings highlight the need to identify key noise sources and assess their impacts on marine life to effectively manage oceanic ecosystems.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0020.004
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.045
GPT teacher head0.320
Teacher spread0.276 · 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 teacher head, not a consensus.

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
Published2022
Admission routes1
Has abstractyes

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