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Record W1971208165 · doi:10.1117/1.3484261

Integrating spheres for improved skin photodynamic therapy

2010· article· en· W1971208165 on OpenAlexaff
Diana L. Glennie

Bibliographic record

VenueJournal of Biomedical Optics · 2010
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsPhotodynamic therapyOpticsMaterials scienceIntegrating sphereActinic keratosisDosimetryBiomedical engineeringSPHERESLaserReflectivityOptoelectronicsMedicineNuclear medicineChemistryPhysics

Abstract

fetched live from OpenAlex

The prescribed radiant exposures for photodynamic therapy (PDT) of superficial skin cancers are chosen empirically to maximize the success of the treatment while minimizing adverse reactions for the majority of patients. They do not take into account the wide range of tissue optical properties for human skin, contributing to relatively low treatment success rates. Additionally, treatment times can be unnecessarily long for large treatment areas if the laser power is not sufficient. Both of these concerns can be addressed by the incorporation of an integrating sphere into the irradiation apparatus. The light fluence rate can be increased by as much as 100%, depending on the tissue optical properties. This improvement can be determined in advance of treatment by measuring the reflectance from the tissue through a side port on the integrating sphere, allowing for patient-specific treatment times. The sphere is also effective at improving beam flatness, and reducing the penumbra, creating a more uniform light field. The side port reflectance measurements are also related to the tissue transport albedo, enabling an approximation of the penetration depth, which is useful for real-time light dosimetry.

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)0.001
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 score0.429
Threshold uncertainty score0.454

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.334
Teacher spread0.320 · 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

Citations4
Published2010
Admission routes1
Has abstractyes

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