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A new version of the SWIFT platform for waves, currents, and turbulence in the ocean surface layer

2019· article· en· W2999344511 on OpenAlexaff
Jim Thomson, Melissa Moulton, Alex de Klerk, Joe Talbert, Maricarmen Guerra, Sam Kastner, Madison M. Smith, Seth Zippel, Sven Nylund

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSwiftTurbulenceSurface waveWind waveGeologySurface layerLayer (electronics)MeteorologyComputer sciencePhysicsOceanographyMaterials scienceTelecommunicationsAstrophysicsNanotechnology

Abstract

fetched live from OpenAlex

The Surface Wave Instrument Float with Tracking (SWIFT) is a freely drifting platform for measurements of waves, currents, and turbulence in the ocean surface layer. This platform has been used globally to study wave breaking, wave-current interactions, and waves in ice. A new version (v4) of the buoy has recently been developed and demonstrated in the Office of Naval Research “Langmuir Circulations” field campaign along the California coast (2017). The new version is built around a 5-beam Acoustic Doppler Current Profiler (Nortek Signature 1000) with a multi-pulse coherent mode for high-resolution turbulence measurements. The new Doppler profiler enables estimates of the turbulent dissipation rate down to 3.5 m below waves, compared with 0.5 m in the previous version, and can measure a much larger range of turbulence levels than the previous version. The new version also uses a broadband Doppler mode to profile the mean currents down to 20 m. Mean Eulerian velocity profiles are estimated from the wave-averaged profiler velocities by applying a wave-following bias correction that scales with the Stokes drift and has twice the vertical decay scale. Finally, the new version supports real-time telemetry of raw sea surface elevations for reconstruction of individual waves by processing a coherent array of multiple SWIFTs, with applications for short-range wave-by-wave forecasting. These combined improvements to the platform are intended to advance understanding of wave processes and applications in the ocean surface layer.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.189

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.207
Teacher spread0.195 · 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.

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

Citations31
Published2019
Admission routes1
Has abstractyes

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