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Record W2333191000 · doi:10.1109/embc.2014.6944428

Design of a single-fiber, wavelength-resolved system for monitoring deep tissue oxygenation

2014· article· en· W2333191000 on OpenAlexaff
Linhui Yu, Kartikeya Murari

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsOpticsOptical fiberSpectrometerFiberDetectorBeam splitterPolarizerMaterials sciencePhotodiodeWavelengthOptoelectronicsImaging phantomPhoton countingPhysicsLaser

Abstract

fetched live from OpenAlex

We propose a single-fiber, zero source-detector separation system with wavelength-resolved detection for measuring oxygen saturation in deep brain structures. The system consists of a white light emitting diode (LED) source, optics to couple light into a 240-μm-diameter fiber, a beam splitter to separate the collected from the delivered photons and a spectrometer for detection. Depth resolution is achieved by inserting the fiber, comparable in size to microelectrodes used for electrophysiology, into the tissue of interest. Since most of the diffuse reflected light travels through a small volume at the tip of the fiber, this arrangement allows efficient collection of signal. Fresnel reflections are minimized using polarizers. Monte Carlo simulations across 400-1000 nm indicate that ~0.5% of the incident light can be collected and effectively interrogate a ~0.02 mm(3) volume at the fiber tip. System design, characterization data and phantom experiments using an absorptive dye in scattering media are presented. The simple nature of the instrumentation can potentially lead to a miniaturized system capable of detecting oxygen saturation in deep brain structures in freely-moving animals.

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: Methods · Consensus signal: none
Teacher disagreement score0.625
Threshold uncertainty score0.333

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 head0.032
GPT teacher head0.307
Teacher spread0.275 · 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
GenreMethods

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
Published2014
Admission routes1
Has abstractyes

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