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Record W2188738027

Physical mechanisms underlying the acoustic signature of breaking waves

2015· article· en· W2188738027 on OpenAlexaffvenue
Cameron Dallas, Cristina Tollefsen

Bibliographic record

VenueCanadian acoustics · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsDefence Research and Development CanadaUniversity of Victoria
Fundersnot available
KeywordsBreaking waveAcousticsNoise (video)GeologyAmbient noise levelSound pressureSeismologyPhysicsSound (geography)Wave propagationOpticsComputer science
DOInot available

Abstract

fetched live from OpenAlex

The characteristic sound of breaking waves is an integral component of the ambient noise along the coastline.  The underwater noise generation from breaking waves has been thoroughly studied, but very little work has been published on the airborne noise caused by breaking waves. Acoustic recordings from a field study were analyzed in an attempt to determine the noise generation mechanisms. A microphone was deployed at Osborne Head, Nova Scotia from June – August 2011 on a grassy cliff above a beach with abundant breaking wave activity. Photographs, weather and ocean wave data were collected to assist in interpreting the audio recordings. Individual breaking wave events were located in the data and their third-octave band spectra were analyzed. The sound pressure levels in the 50 to 315 Hz bands increased by 5 to 20 dB as the wave breaking occurred. The frequency range of the disturbance was used to postulate the breaking wave mechanisms which give rise to its characteristic sound: falling water impacting the surface and the large collapsing air volume present for wave heights greater than 1 m.

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 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: none
Teacher disagreement score0.558
Threshold uncertainty score0.949

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.053
GPT teacher head0.268
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

Citations0
Published2015
Admission routes2
Has abstractyes

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