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Record W2034831391 · doi:10.1029/2011jc007113

Observations of the vertical structure of turbulent oscillatory boundary layers above fixed roughness beds using a prototype wideband coherent Doppler profiler: 1. The oscillatory component of the flow

2011· article· en· W2034831391 on OpenAlexaff
Alex E. Hay, Len Zedel, Richard Cheel, Jeremy Dillon

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsMemorial University of NewfoundlandDalhousie University
Fundersnot available
KeywordsAcoustic Doppler current profilerWidebandDoppler effectTurbulenceOpticsGeologyPhysicsAcousticsMechanics

Abstract

fetched live from OpenAlex

Results are presented from an experimental investigation of rough turbulent oscillatory boundary layers using a prototype wideband bistatic coherent Doppler profiler. The profiler operates in the 1.2 MHz to 2.3 MHz frequency band and uses software‐defined radio technologies for digital control of the frequency content and shape of the transmit pulse and for digital complex demodulation of the received signals. Velocity profiles are obtained at sub‐millimeter range resolution and 100 Hz profiling rates (each profile being an ensemble average of 10 pulse pairs). The measurements were carried out above beds of fixed sand or gravel particles, with median grain diameters of 0.37 mm and 3.9 mm, respectively, oscillating sinusoidally at a 10 s period through excursions of 0.75 m to 1.5 m. The resulting vertical profiles of horizontal velocity magnitude and phase, with the vertical axis scaled by ℓ = κu ∗m / ω , are comparable to similarly scaled profiles obtained using laser Doppler anemometry by Sleath (1987) and Jensen (1988). A key objective of the comparisons between the previous experiments and those reported here was to establish how close to the bed reliable velocity measurements can be made with the sonar. This minimum distance above the bed is estimated to be 5 ± 1 mm, a value approaching the 3 to 4 mm limit set by the path of least time.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.673

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.051
GPT teacher head0.270
Teacher spread0.218 · 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

Citations27
Published2011
Admission routes1
Has abstractyes

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