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Record W1966571921 · doi:10.1063/1.2219102

Internal wave instability: Wave-wave versus wave-induced mean flow interactions

2006· article· en· W1966571921 on OpenAlexaff
Bruce Sutherland

Bibliographic record

VenuePhysics of Fluids · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhysicsInstabilityModulational instabilityInternal waveConvective instabilityMechanicsAmplitudeGravity waveMechanical waveWave packetBreaking waveWave propagationSurface waveAccelerationClassical mechanicsLongitudinal waveOpticsAtomic physics

Abstract

fetched live from OpenAlex

In continuously stratified fluid, vertically propagating internal gravity waves of moderately large amplitude can become unstable and possibly break due to a variety of mechanisms including (with some overlap) modulational instability, parametric subharmonic instability (PSI), self-acceleration, overturning, and convective instability. In PSI, energy from primary waves is transferred, for example, to waves with half frequency. Self-acceleration refers to a mechanism whereby a wave packet induces a mean flow (analogous to the Stokes drift of surface waves) that itself advects the waves until they become convectively unstable. The simulations presented here show that self-acceleration dominates over parametric subharmonic instability if the wave packet has a sufficiently small vertical extent and sufficiently fast frequency.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.231
Teacher spread0.196 · 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

Citations45
Published2006
Admission routes1
Has abstractyes

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