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Record W2095068905 · doi:10.1121/1.4744577

High-frequency ocean ambient sound: Estimating wind speed using a 150-kHz ADCP

2001· article· en· W2095068905 on OpenAlexaff
Len Zedel

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSound (geography)Wind speedAmbient noise levelSpeed of soundEnvironmental scienceAcousticsGeologyNoise (video)Frequency spectrumMeteorologyPhysicsOceanographySpectral densityComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Ocean ambient sound is well correlated with wind speed for frequencies between 2 and 50 kHz. At higher frequencies it is conventional wisdom that thermal noise will dominate the wind-generated sound. Data are presented showing that background sound levels recorded by a 150-kHz ADCP demonstrate strong correlation with wind speed and with independent measurements of ambient sound (below 70-kHz frequency). When the ADCP data are calibrated using scaling factors available from the manufacturer, the observed 150-kHz sound levels are consistent with the expected ≂20 dB/decade slope of the high-frequency ambient sound spectrum. Using calibrations based on two independent deep ocean deployments, 150-kHz ADCP background sound levels can be used to estimate ocean wind speeds with an accuracy of 1.5±1.5 m s−1 for wind speeds up to 15 m s−1. [This research was funded by R. D. Instruments.]

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.031
GPT teacher head0.275
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2001
Admission routes1
Has abstractyes

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