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Record W1974557614 · doi:10.1121/1.4783461

Marine mammal noise exposure criteria: Initial scientific recommendations.

2009· article· en· W1974557614 on OpenAlexaff
Brandon L. Southall, Ann E. Bowles, William T. Ellison, James J. Finneran, Roger L. Gentry, Charles R. Greene, David Kastak, Darlene R. Ketten, James H. Miller, Paul E. Nachtigall, W. John Richardson, Jeànette A. Thomas, Peter L. Tyack

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsLGL (Canada)
Fundersnot available
KeywordsMarine mammalSound exposureNoise exposureNoise (video)ExtrapolationEnvironmental scienceDisturbance (geology)BioacousticsCumulative effectsRange (aeronautics)AudiologySound (geography)Hearing lossMedicineBiologyEcologyComputer scienceStatisticsAcousticsMathematicsPhysics

Abstract

fetched live from OpenAlex

An expert panel reviewed the expanding literature on marine mammal (cetacean and pinniped) auditory and behavioral responses to sound exposure to develop comprehensive, scientifically based noise exposure criteria [Aquatic Mammals 33(4)]. They used precautionary extrapolation procedures to predict exposure levels above which adverse effects (both physical and behavioral) could be expected. Due to the paucity of data on long-term exposures, criteria were developed for single exposure events only. Marine mammals were broken into functional hearing groups. Exposure types were lumped into three broad classes (single pulses, multiple pulses, and nonpulses). Levels estimated to induce permanent noise-induced hearing loss were determined for each of 15 sound type/animal group combinations. For example, injury criteria for pinnipeds in water exposed to multiple pulses were 186 dB re 1 μPa2 -s (weighted SEL) and 218 dBpk re 1 μPa (unweighted peak SPL). Discrete behavioral disturbance thresholds could only be determined for exposure to single pulses. For other exposures, available data on behavioral responses were ranked by severity and significance. This severity scaling and the resulting conclusions will be described. New research required to improve criteria and to assess cumulative and ecosystem-level effects will also be considered, along with current policy and/or regulatory applications.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.275
Teacher spread0.257 · 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 designNot applicable
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

Citations90
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicMarine animal studies overviewFrench-language works237,207