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Record W2035052746 · doi:10.1055/s-2005-872411

Applications of Aminolevulinic Acid-Based Photodynamic Therapy in Cosmetic Facial Plastic Practices

2005· review· en· W2035052746 on OpenAlexaff
Kristina Zakhary, David A.F. Ellis

Bibliographic record

VenueFacial Plastic Surgery · 2005
Typereview
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineRosaceaDermatologyPhotodynamic therapyAcneMelasmaFood and drug administrationPharmacology

Abstract

fetched live from OpenAlex

Photodynamic therapy (PDT) using aminolevulinic acid (ALA) is a promising new technique that is being studied extensively and used in a variety of cosmetic facial plastic arenas. These applications include U.S. Food and Drug Administration-approved treatment of premalignant and malignant skin conditions, as well as off-label uses for photorejuvenation, and the treatment of acne vulgaris, sebaceous gland hyperplasia, rosacea, and hirsutism. This article reviews the interplay of factors that contribute to the appearance of actinically damaged or photoaged skin, also known as dermatoheliosis. This is followed by a brief review of the mechanisms of action of ALA-based PDT and some of its cosmetic facial plastic uses.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.085
GPT teacher head0.398
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations25
Published2005
Admission routes1
Has abstractyes

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