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Record W4315874448 · doi:10.1364/boe.484257

Localized transverse flow measurement with dynamic light scattering line-scan OCT

2023· article· en· W4315874448 on OpenAlexafffund
Le Han, Bingyao Tan, Leopold Schmetterer, Kostadinka Bizheva

Bibliographic record

VenueBiomedical Optics Express · 2023
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsUniversity of Waterloo
FundersMedical Research CouncilNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundNational Medical Research CouncilNational Research Foundation SingaporeMedical Research Council CanadaCanadian Institutes of Health ResearchUniversity of WaterlooNational Research Foundation
KeywordsOpticsOptical coherence tomographyTransverse planeLine (geometry)Light scatteringFlow (mathematics)ScatteringMaterials sciencePhysicsMedicineRadiology

Abstract

fetched live from OpenAlex

A novel decorrelation-based approach for measuring localized transverse flow velocity using line-scan (LS) optical coherence tomography (OCT) is proposed. The new approach allows for separation of the flow velocity component along the line-illumination direction of the imaging beam from other orthogonal velocity components, from particle diffusion motion, and from noise-induced distortion in the OCT signal’s temporal autocorrelation. The new method was verified by imaging flow in a glass capillary and a microfluidic device and mapping the spatial distribution of the flow velocity within the beam’s illumination plane. This method can be extended in the future to map the three-dimensional flow velocity fields for both ex -vivo and in-vivo applications.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.855
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.231
Teacher spread0.214 · 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 designSimulation or modeling
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

Citations2
Published2023
Admission routes2
Has abstractyes

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