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Record W1973118681 · doi:10.1121/1.4787526

A comparison of two observations of compressional wave velocity dispersion in marine sediments

2006· article· en· W1973118681 on OpenAlexaff
Charles W. Holland, Altan Turgut, Jan Dettmer, Stan E. Dosso

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsDispersion (optics)BroadbandAttenuationSeabedAcousticsGeologyReflection (computer programming)Velocity dispersionLongitudinal waveSeismologyWave propagationOceanographyPhysicsOpticsComputer science

Abstract

fetched live from OpenAlex

Compressional velocity dispersion exists in all marine sediments. If the dispersion is great enough, it may play a significant role in acoustic interaction with the seabed. On the other hand, if dispersion is weak, seabed models and databases can be substantially simpler. The ocean acoustics community is divided on this issue, in part because of the lack of observations. Here we compare two recent methods for measuring dispersion. One technique measures the broadband reflection coefficient (frequency dependence of the critical angle) and thus infers the velocity dispersion. The other technique measures time of flight in an in situ probe over a broadband of frequencies. Measurements on New Jersey Shelf (STRATAFORM area) are compared and implications for the frequency dependence of the compressional wave attenuation are discussed. [Work supported by the Office of Naval Research and NATO Undersea Research Centre.]

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)0.001
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.046
GPT teacher head0.303
Teacher spread0.256 · 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
Published2006
Admission routes1
Has abstractyes

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