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Record W4365457819 · doi:10.1093/jcde/qwad033

Laser–tissue interaction simulation considering skin-specific data to predict photothermal damage lesions during laser irradiation

2023· article· en· W4365457819 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

VenueJournal of Computational Design and Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsUniversité Laval
FundersNational Research Foundation of KoreaMinistry of Trade, Industry and EnergyMinistry of Science and ICT, South KoreaMinistry of Food and Drug SafetyKorea Medical Device Development FundMinistry of EducationMinistry of Health and Welfare
KeywordsPhotothermal therapyLaserMonte Carlo methodOptical coherence tomographyMaterials scienceIrradiationAttenuation coefficientAbsorption (acoustics)OpticsBiomedical engineeringRadiationBiological systemMathematicsComposite materialPhysicsNanotechnologyEngineeringStatistics

Abstract

fetched live from OpenAlex

Abstract This study aimed to develop a simulation model that accounts for skin-specific properties in order to predict photothermal damage during skin laser treatment. To construct a computational model, surface geometry information was obtained from an optical coherence tomography image, and the absorption coefficient of the skin was determined through spectrophotometry. The distribution of the internal light dose inside the skin medium was calculated using the light propagation model based on the Monte Carlo method. The photothermal response due to the absorption of laser light was modeled by a finite difference time domain model to solve the bio-heat transfer equation. The predicted depth and area of the damaged lesions from the simulation model were compared to those measured in ex vivo porcine skin. The present simulation model gave acceptable predictions with differences of approximately ∼10% in both depth and area.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.471
Threshold uncertainty score0.639

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 communication0.0000.001
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 head0.047
GPT teacher head0.277
Teacher spread0.231 · 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