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Record W2518339601 · doi:10.1109/iscas.2016.7527238

Time-resolved reflectance using short source-detector separation

2016· article· en· W2518339601 on OpenAlexaff
Sreenil Saha, Frédéric Lesage, Mohamad Sawan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Optical Sensing Technologies
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsDetectorOpticsPhotonPhysicsPenetration depthPhoton countingRange (aeronautics)Materials science

Abstract

fetched live from OpenAlex

In Optical Time-Resolved Reflectance, a pair of injecting and collecting optical fibers are placed at a fixed source-detector separation from each other typically in the range of 20 to 40mm limited by the detector dynamic range. To increase the sensitivity to higher penetration depth of investigation, the source and the detector separation should be small. We first show with simulation results that short source-detector separations results in the detection of a higher number of photons coming from a greater depth. However, at these shorter distances the number of early arriving photons also increase (mainly coming from the skull and scalp regions in brain imaging) which is a constraint. To reject the early arriving photons we need a gated detector to enable detections at specified time windows. We then confirm these results in an experimental study using a simplified photon detection scheme. The dependency of the photon counts on the gate window and the source-detector separation is analyzed. We conclude that placing the laser source and the detector quite close to each other is an option to consider for the design of optodes so as to improve the image quality in various biomedical appications.

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: Empirical · Consensus signal: none
Teacher disagreement score0.524
Threshold uncertainty score0.357

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 head0.022
GPT teacher head0.304
Teacher spread0.282 · 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
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

Citations5
Published2016
Admission routes1
Has abstractyes

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