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Record W1999306241 · doi:10.1029/2004jc002537

Topographic amplitude dependence of internal wave generation by tidal forcing over idealized three‐dimensional topography

2005· article· en· W1999306241 on OpenAlexaff
James Munroe, Kevin G. Lamb

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSeamountAmplitudeEnergy fluxGeologyRidgeFlux (metallurgy)GeophysicsInternal waveGeodesyPhysicsOceanographyOptics

Abstract

fetched live from OpenAlex

This numerical study using the Princeton Ocean Model investigates the conversion of energy from an eastward propagating surface tide to the internal wave field as an oscillating tidal current flows over and around idealized three‐dimensional Gaussian seamounts. In particular, the relationship between the energy flux in the internal wave field and the height of the topography is explored using a range of horizontal aspect ratios. In agreement with theory, the energy flux is found to increase as the square of the topographic amplitude h o for subcritical topography. For supercritical topographies the functional relationship is more complex aspect ratio dependent. It increases more rapidly than h o 2 for near‐critical topography. For larger circular seamounts the energy flux increases much more slowly, with the rate of increase dropping with amplitude. As the seamounts are elongated in the cross‐tidal wave (north‐south) direction the energy flux increases more rapidly with height and, for a two‐dimensional ridge, increases as approximately h o 2.2 . The directional dependence of the energy flux also depends on the aspect ratio and amplitude of the seamount. For circular seamounts, energy flux has its maximum in directions between 20° and 45° counterclockwise from the east‐west axis (Northern Hemisphere). For elongated seamounts the energy flux is directed in the east‐west direction.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.289
Teacher spread0.259 · 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 teacher head, not a consensus.

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

Citations44
Published2005
Admission routes1
Has abstractyes

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