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Record W2005767464 · doi:10.1134/s1054660x12040251

Quantification of glucose levels in flowing blood using M-mode swept source optical coherence tomography

2012· article· en· W2005767464 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLaser Physics · 2012
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsToronto Metropolitan UniversityUniversity Health NetworkUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsOptical coherence tomographySpeckle patternDecorrelationOpticsMaterials scienceDiffusionScatteringCoherence (philosophical gambling strategy)Blood flowBiomedical engineeringPhysicsMathematicsMedicine

Abstract

fetched live from OpenAlex

The increase of glucose levels in blood changes the viscosity of flowing fluids and shape of the erythrocytes. Both of these can affect the details of light scattering as can be quantified via decorrelation times measured by optical coherence tomography (OCT). The relative contributions of these competing effects have been studied by examining the motion dynamics of deformable asymmetrical (red blood cells, RBCs with ∼7 μm diameter and ∼2 μm thickness) and non deformable symmetrical (polystyrene microspheres, PSM with 1.4 μm diameter) flowing scattering particles. The fluid flow under the action of gravity was modulated by changing the glucose concentrations. Quantitative analysis of the OCT’s M-mode autocorrelation functions enabled the derivations of the translational diffusion coefficients. These systematic studies are aimed at eventual tissue imaging scenarios with speckle-variance OCT to obtain local glucose concentrations maps.

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.

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 score0.088
Threshold uncertainty score0.814

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 head0.033
GPT teacher head0.270
Teacher spread0.237 · 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