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Record W2489958963 · doi:10.1039/9781847555281

Photodynamic Therapy with ALA

2006· book· en· W2489958963 on OpenAlexaff
Hugh Barr, Christian Betz, Alison Curnow, Mathias K. Fehr, Peter Hillemanns, René Hornung, J. C. Kennedy, Andreas Leunig, Zvi Malik, Helmut Messmann, Verena Schleyer, Walter Stummer, Rolf‐Markus Szeimies, Raphaela Waidelich

Bibliographic record

Venuenot available
Typebook
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsPhotodynamic therapyPhotosensitizerMedicineOtorhinolaryngologyDermatologyCancer researchMedical physicsChemistrySurgeryPhotochemistry

Abstract

fetched live from OpenAlex

Photodynamic therapy (PDT) is increasingly being used amongst health practitioners in combating a variety of diseases. One common strategy used during this light activated process is to induce the accumulation of significant amounts of a photosensitising agent in the diseased tissue. The naturally occurring amino acid 5-aminovulinic acid (ALA) is used to produce high levels of the photosensitizer, Protoprophyin IX, in the therapy known as ALA-PDT. Written by experts in the field Photodynamic therapy with ALA outlines a variety of clinical approaches to the topic, outlining current applications. These include the use of ALA-PDT and ALA-FD (fluorescence diagnosis) in the areas of dermatology, urology, brain, otorhinolaryngology, gynaecology and gastroenterology. Also included is a chapter that comprehensively reviews the scientific principles of ALA-PDT. Primarily aimed at a clinical audience Photodynamic therapy with ALA should provide a comprehensive review and useful insight into ALA-PDT.

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: Other · Consensus signal: Other
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0260.020

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 head0.013
GPT teacher head0.285
Teacher spread0.272 · 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
GenreOther

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

Citations24
Published2006
Admission routes1
Has abstractyes

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