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Record W2895783352 · doi:10.1121/1.5068019

Short-term fluctuations in the ambient noise field at an Arctic chokepoint horizontal line array

2018· article· en· W2895783352 on OpenAlexaffabout
Dugald Thomson, David R. Barclay, Stan E. Dosso, Garry J. Heard

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsUniversity of VictoriaDalhousie University
Fundersnot available
KeywordsAmbient noise levelNoise (video)ArcticEnvironmental scienceHydrophoneSonarAcousticsInletOceanographyMeteorologyGeologySound (geography)Computer scienceGeographyPhysics

Abstract

fetched live from OpenAlex

The Arctic is a region known for high variance in both ambient noise levels and local sound propagation conditions, and is currently experiencing an historic increase in shipping traffic, resulting in an acoustic environmental that is changing so rapidly that the sparse ambient noise data available from decades-old studies have been rendered obsolete. Renewed interest in Arctic acoustics have provided fresh noise data at northern sites, and in the summer of 2015 Defence R&D Canada collected a continuous two-week recording of the 48-hydrophone Northern Watch horizontal line array at Gascoyne Inlet. Over the ice-free study period, numerous ship passes, weather events, and anomalies were observed in the high-quality acoustic recordings. In this paper, spectral fluctuations, directionality, and correlation with ship tracks and weather observations in the noise data are analyzed to help improve the applicability of operational arctic noise models supporting sonar performance.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.664

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)0.0010.000

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 head0.024
GPT teacher head0.281
Teacher spread0.258 · 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
Published2018
Admission routes2
Has abstractyes

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