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Record W2075346606 · doi:10.1121/1.4786187

Effects of riverine seismic air-gun exposure on fish hearing

2006· article· en· W2075346606 on OpenAlexaff
David A. Mann, Peter A. Cott, Bruce W. Hanna, Alex MacGillivray, Melanie E. Austin, Michael L. Smith, Arthur N. Popper

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsPikeEsoxCoregonusFish <Actinopterygii>Environmental scienceRiver deltaAbsolute threshold of hearingFisheryBiologyDeltaAudiologyPhysics

Abstract

fetched live from OpenAlex

Seismic airguns produce considerable amounts of acoustic energy that have the potential to affect marine life. This study investigated the effects of exposure to an airgun array in the Mackenzie River Delta on the hearing of three fish species: northern pike (Esox lucius), broad whitefish (Coregonus nasus), and lake chub (Couesius plumbeus). Fish were placed in cages in 1.9 m of water and exposed to 5 or 20 airgun shots, while controls were placed in the same cage but without airgun exposure. Hearing in both exposed and control fish were then tested using auditory evoked potentials (AEPs). Threshold shifts were found for exposed fish as compared to controls in the northern pike and lake chub, with recovery within 24 h of exposure, while there was no threshold shift in the broad whitefish. It is concluded that these three species are not likely to be substantially impacted by exposure to a 2D airgun array used in a river seismic survey. Care must be taken in extrapolation to other species in other environments and to fishes exposed to airguns in 3D tests or where the animals are exposed to a larger number of airgun shots over a longer period of time.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score0.258

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.225
Teacher spread0.215 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicUnderwater Acoustics ResearchFrench-language works237,207