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Record W4394579038 · doi:10.1175/jpo-d-23-0180.1

The Generation of Superinertial Coastally Trapped Waves by Scattering at the Coast

2024· article· en· W4394579038 on OpenAlexaff
Ruth Musgrave, D. Winters, Varvara Zemskova, James A. Lerczak

Bibliographic record

VenueJournal of Physical Oceanography · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsDalhousie University
FundersNational Science Foundation
KeywordsGeologyScatteringGeophysicsOceanographyKelvin waveClimatologyBreaking waveAtmospheric sciencesMeteorologyPhysicsWave propagationOptics

Abstract

fetched live from OpenAlex

Abstract A series of idealized numerical simulations is used to examine the generation of mode-one superinertial coastally trapped waves (CTWs). In the first set of simulations, CTWs are resonantly generated when freely propagating mode-one internal tides are incident on the coast such that the angle of incidence of the internal wave causes the projected wavenumber of the tide on the coast to satisfy a triad relationship with the wavenumbers of the bathymetry and the CTW. In the second set of simulations, CTWs are generated by the interaction of the barotropic tide with topography that has the same scales as the CTW. Under resonant conditions, superinertial coastally trapped waves are a leading order coastal process, with alongshore current magnitudes that can be larger than the barotropic or internal tides from which they are generated.

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 score0.005
Threshold uncertainty score0.009

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 science0.0010.001
Research integrity0.0010.000
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 head0.011
GPT teacher head0.216
Teacher spread0.205 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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