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Record W2170711136 · doi:10.1175/2009jtecho696.1

Acoustic Detection of Oceanic Double-Diffusive Convection: A Feasibility Study

2009· article· en· W2170711136 on OpenAlexafffund
Tetjana Ross, Andone C. Lavery

Bibliographic record

VenueJournal of Atmospheric and Oceanic Technology · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaOcean Life Institute, Woods Hole Oceanographic InstitutionDalhousie UniversityWoods Hole Oceanographic Institution
KeywordsScatteringConvectionDouble diffusive convectionRange (aeronautics)GeologyComputational physicsGeophysicsMaterials sciencePhysicsOpticsMeteorologyNatural convection

Abstract

fetched live from OpenAlex

Abstract The feasibility of using high-frequency acoustic scattering techniques to map the extent and evolution of the diffusive regime of double-diffusive convection in the ocean is explored. A scattering model developed to describe acoustic scattering from double-diffusive interfaces in the laboratory, which accounted for much of the measured scattering in the frequency range from 200 to 600 kHz, is used in conjunction with published in situ observations of diffusive-convection interfaces to make predictions of acoustic scattering from oceanic double-diffusive interfaces. Detectable levels of acoustic scattering are predicted for a range of different locations in the world’s oceans. To corroborate these results, thin acoustic layers detected near the western Antarctic Peninsula using a multifrequency acoustic backscattering system are shown to be consistent with scattering from diffusive-convection interfaces.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.224
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 source (direct Gemma or distilled Codex), 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

Citations7
Published2009
Admission routes2
Has abstractyes

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