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Record W4378232039 · doi:10.1111/mms.13028

Vocal count responses of narwhals to bulk carrier noise in Milne Inlet, Nunavut, Canada

2023· article· en· W4378232039 on OpenAlexafffundabout
Crystal L. Radtke, John M. Terhune, Héloïse Frouin‐Mouy, Philippe A. Rouget

Bibliographic record

VenueMarine Mammal Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsWSP (Canada)University of New Brunswick
FundersUniversity of New Brunswick
KeywordsAmbient noise levelNoise (video)InletHuman echolocationEnvironmental scienceAcousticsHabituationSound pressureSound (geography)OceanographyPhysicsAudiologyGeologyComputer scienceMedicine

Abstract

fetched live from OpenAlex

Abstract Concerns were raised about possible behavioral disturbance to narwhals ( Monodon monoceros ) when exposed to shipping noise in Milne Inlet, Baffin Island, Canada. We deployed passive acoustic recorders in August and September 2018 and 2019, along and adjacent to the nominal shipping corridor. We measured broadband (0.01–25 kHz) sound pressure levels (SPL) after correcting for the auditory weighting function of high frequency cetaceans. Received SPLs and counts of Whistles, Buzzes, and Knocks were compared in a before‐during‐after study of individual bulk carrier transits, relative to periods with no ships. Narwhal call counts were generally lower once bulk carriers were within line‐of‐sight, including when ship noise levels were just above ambient noise levels. Call counts varied both “before” and “after” individual bulk carriers passed by the recorders. There was no evidence of a behavioral threshold SPL below which a response did not occur. We did not observe call count reductions to the same extent in 2019 compared to 2018 as higher ambient noise levels in 2019 likely masked some individual ship noise. There was no evidence of habituation or sensitization to the bulk carrier noise within or between years. Continued acoustic monitoring is recommended, especially if bulk carrier transits increase.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.116
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.004
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 head0.015
GPT teacher head0.247
Teacher spread0.231 · 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

Citations4
Published2023
Admission routes3
Has abstractyes

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