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Record W2065252975 · doi:10.1088/0031-9155/46/2/307

A diffusion theory model of spatially resolved fluorescence from depth-dependent fluorophore concentrations

2001· article· en· W2065252975 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

VenuePhysics in Medicine and Biology · 2001
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsUniversity of TorontoOntario Institute for Cancer ResearchCancer Care OntarioMcMaster UniversityMcMaster University Medical CentreHamilton Regional Laboratory Medicine ProgramJuravinski Cancer Centre
FundersNational Cancer Institute
KeywordsFluorophorePhotobleachingFluorescenceMonte Carlo methodPhoton diffusionMaterials scienceExcitationDiffusionOpticsPhotonTwo-photon excitation microscopyPhoton transport in biological tissuePhotodynamic therapyBiological systemBiomedical engineeringMolecular physicsChemistryPhysicsLight sourceDirect simulation Monte Carlo

Abstract

fetched live from OpenAlex

A photon diffusion model has been developed to calculate the steady-state spatially resolved fluorescence from pencil beam excitation in layered tissue. The model allows the calculation of both the excitation reflectance and the fluorescence escape for an arbitrary continuous depth distribution of tissue optical properties and fluorophore concentration. The validity of this model was verified by comparison with Monte Carlo simulations and experimental measurements using phantoms with tissue-like optical properties. The potential usefulness of the spatially resolved fluorescence was explored using the model and simulations of realistic drug distributions. It was shown that using this technique it may be possible to quantify the diffusion of a topically administered drug into the skin, or the photobleaching of a sensitizer during photodynamic therapy.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.698
Threshold uncertainty score0.312

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 head0.124
GPT teacher head0.387
Teacher spread0.263 · 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