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Record W2131431204 · doi:10.1029/2009jc006027

A wave‐driven jet over a rocky shoal

2010· article· en· W2131431204 on OpenAlexafffund
Ryan P. Mulligan, Alex E. Hay, Anthony J. Bowen

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsDalhousie University
FundersOffice of Naval ResearchNatural Sciences and Engineering Research Council of CanadaCanadian Foundation for Climate and Atmospheric Sciences
KeywordsShoalGeologyBathymetryBreaking waveRidgeWave modelJet (fluid)Current (fluid)GeomorphologySeismologyOceanographyWave propagationMeteorologyMechanicsPhysics

Abstract

fetched live from OpenAlex

Field observations and model simulations are presented of flow generated by waves breaking over a shoal at the entrance to a shallow bay. The shoal is composed of a series of steep and narrow bedrock ridges with depths of 2–8 m at the ridge crests. Observations from instruments on the shoal indicated peak significant wave heights during a storm event were 2.4–4.0 m across the observation sites; this spatial variability is due to wave breaking over the ridges. The 2‐D depth‐averaged hydrodynamic model Delft3D, coupled to the wave model SWAN, was used to simulate the waves and wave‐driven flow over the shoal and throughout the entire bay with a nested fine grid (5 m resolution) to resolve the shoal bathymetry. The model predicts a well‐defined jet behind the shoal, with mean axial speeds of 0.4–0.7 m/s. The observations indicate maximum speeds behind the shoal of 0.3–0.4 m/s, exceeding the maximum tidal current speed by more than a factor of 4, that are consistent in timing and direction with the model predictions. The model overpredicts wave breaking over the steep slopes and as a result the current speeds are overestimated.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.023
GPT teacher head0.286
Teacher spread0.263 · 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

Citations26
Published2010
Admission routes2
Has abstractyes

Explore more

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