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Record W2036062819 · doi:10.1364/ao.49.003140

High-velocity-flow imaging with real-time Doppler optical coherence tomography

2010· article· en· W2036062819 on OpenAlexaff
Richard Villey, Lionel Carrion, Dominic Morneau, Caroline Boudoux, R. Maciejko

Bibliographic record

VenueApplied Optics · 2010
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsOptical coherence tomographyOpticsDoppler effectFlow velocityLaminar flowPhysicsAliasingTomographyCoherence (philosophical gambling strategy)TurbulenceGroup velocityFlow (mathematics)MechanicsComputer scienceFilter (signal processing)

Abstract

fetched live from OpenAlex

We present a real-time time-domain Doppler optical coherence tomography (OCT) system based on the zero-crossing method for velocity measurements of fluid flows with attainable velocities up to 10 m/s. In the current implementation, one-dimensional and two-dimensional velocity profiles of fluid flows ranging from 1 cm/s to more than 3 m/s were obtained for both laminar and turbulent flows. The line rate was approximately 500 Hz, and the images were treated in real time. This approach has the advantage of providing reliable velocity maps free from phase aliasing or other artifacts common to several OCT systems. The system is particularly well suited for investigating complex velocity profiles, especially in the presence of steep velocity gradients.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.004
GPT teacher head0.194
Teacher spread0.190 · 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 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

Citations3
Published2010
Admission routes1
Has abstractyes

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