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High Frequency Surface Wave Radar Studies of Inertial Oscillations

2024· article· en· W4404688514 on OpenAlexaff
Joe Craig, Eric W. Gill, Brad de Young

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSurface waveRadarInertial frame of referenceGeologyAcousticsPhysicsAerospace engineeringEngineeringOpticsClassical mechanics

Abstract

fetched live from OpenAlex

Since its inception almost 70 years ago, high frequency (HF) surface wave radar (SWR) has become ubiquitous in ocean physics research. Validation is an important aspect of this relatively new technology and presents interesting chal-lenges. In situ measurements viz.: current meters and drifters yield, respectively, instantaneous Eulerian and Lagrangian current vectors. In contrast, HFSWR vectors are inherently spatio-temporally averaged, thereby confounding direct comparison with in situ results. An additional challenge is that typical standard deviations and means of current velocities are close. We proposed an approach to validation whereby a wind driven one dimensional inertial oscillation model is fitted to the current meter observations. Model radial velocities are then compared against those of a monostatic radar. We found the radar and model velocities to be highly correlated for several days following the excitation of oscillations by a transient wind event.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.336

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 head0.027
GPT teacher head0.256
Teacher spread0.229 · 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 designBench or experimental
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

Citations1
Published2024
Admission routes1
Has abstractyes

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