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Record W1910688352 · doi:10.1002/jbio.201300045

Monte Carlo simulation of<i>in vivo</i>Raman spectral Measurements of human skin with a multi‐layered tissue optical model

2013· article· en· W1910688352 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Biophotonics · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpectroscopy Techniques in Biomedical and Chemical Research
Canadian institutionsVancouver Coastal Health Research InstituteUniversity of British ColumbiaVancouver Coastal HealthBC Cancer Agency
FundersCanadian Institutes of Health Research
KeywordsRaman spectroscopyStratum corneumHuman skinRaman scatteringMonte Carlo methodMaterials scienceOpticsIn vivoDermisEpidermis (zoology)Molecular physicsBiomedical engineeringChemistryPathologyPhysicsAnatomyMedicine

Abstract

fetched live from OpenAlex

Raman photon generation inside human skin and escaping to skin surface were modeled in an eight-layered skin optical model. Intrinsic Raman spectra of different skin layers were determined by microscopy measurements of excised skin tissue sections. Monte Carlo simulation was used to study the excitation light distribution and intrinsic Raman signal distortion caused by tissue reabsorption and scattering during in vivo measurements. The simulation results demonstrated how different skin layers contributed to the observed in vivo Raman spectrum. Using the strongest Raman peak at 1445 cm(-1) as an example, the simulation suggested that the integrated contributions of the stratum corneum layer is 1.3%, the epidermis layer 28%, the dermis layer 70%, and the subcutaneous fat layer 1.1%. Reasonably good matching between the calculated spectrum and the measured in vivo Raman spectra was achieved, thus demonstrated great utility of our modeling method and approaches for help understanding the clinical 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.

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 score0.024
Threshold uncertainty score0.392

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 head0.027
GPT teacher head0.340
Teacher spread0.312 · 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