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Record W2005231413 · doi:10.1063/1.1521524

Experimental and computational aspects of optical property determination of turbid media using frequency-domain laser infrared photothermal radiometry (abstract)

2003· article· en· W2005231413 on OpenAlexaff
Lena Nicolaides, Yan Chen, Andreas Mandelis, I. Alex Vitkin

Bibliographic record

VenueReview of Scientific Instruments · 2003
Typearticle
Languageen
FieldMedicine
TopicInfrared Thermography in Medicine
Canadian institutionsOntario Institute for Cancer ResearchUniversity of TorontoUniversity of New Brunswick
Fundersnot available
KeywordsRadiometryPhotothermal therapyOpticsMaterials scienceMie scatteringInfraredLaserSIGNAL (programming language)Time domainFrequency domainScatteringLight scatteringPhysicsComputer science

Abstract

fetched live from OpenAlex

In this work, the optical and thermal properties of tissue-like materials are measured using frequency-domain infrared photothermal radiometry. This technique is better suited for quantitative multi-parameter optical measurements than the widely used pulsed photothermal radiometry (PPTR), due to the availability of two independent signal channels, amplitude and phase, and the superior signal-to-noise ratio provided by synchronous lock-in detection. A rigorous three-dimensional thermal-wave formulation with a three-dimensional diffuse and coherent photon density-wave source is applied to data from model phantoms. The combined theoretical, experimental, and computational methodology shows good promise with regard to its analytical ability to measure optical properties of turbid media uniquely, as compared to PPTR, which exhibits uniqueness problems. From data sets obtained using calibrated test phantoms, the reduced optical scattering and absorption coefficients were found to be within 20% and 10%, respectively, from the independently derived values using Mie theory and spectrophotometric measurements.

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)0.001
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 score0.040
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.024
GPT teacher head0.293
Teacher spread0.269 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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