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Record W2615974086 · doi:10.1177/1203475417708166

Comparison of the Treatment Guidelines for Actinic Keratosis: A Critical Appraisal and Review

2017· review· en· W2615974086 on OpenAlexaffabout
Patrick Fleming, Stephanie Zhou, Robert Bobotsis, Charles Lynde

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2017
Typereview
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsWestern UniversityLynde Centre for DermatologyUniversity of Toronto
Fundersnot available
KeywordsMedicineActinic keratosisCritical appraisalDermatologyMEDLINEAlternative medicinePathology

Abstract

fetched live from OpenAlex

There are currently several reputable guidelines on the treatment of actinic keratosis (AK) from groups in Canada, the United Kingdom, and Europe. These recommendations, based on evidence or expert consensus, offer clinicians a variety of treatment options for the different clinical presentations of AKs. Although the guidelines are similar in some regards, variations exist in treatment options, duration, and strength of recommendation. Some guidelines also lack input on specific therapies and certain types of AK, such as hypertrophic or thin presentations. The purpose of this article is to review and compare guidelines published by Canadian, UK, and European groups for the management of AKs in patients.

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)0.010
metaresearch head score (Gemma)0.037
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 score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0150.011
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0030.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.457
GPT teacher head0.569
Teacher spread0.112 · 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

Citations27
Published2017
Admission routes2
Has abstractyes

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