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Record W4297359455 · doi:10.1016/j.jdin.2022.09.003

Management of vitiligo with topical janus tyrosine kinase inhibitor therapy: An evidence-based review

2022· article· en· W4297359455 on OpenAlexaff
Abrahim Abduelmula, Asfandyar Mufti, Derrick Chong, Siddhartha Sood, Muskaan Sachdeva, Jensen Yeung

Bibliographic record

VenueJAAD International · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicmelanin and skin pigmentation
Canadian institutionsProbity Medical ResearchHealth Sciences CentreWomen's College HospitalUniversity of TorontoSunnybrook Health Science CentreWestern University
Fundersnot available
KeywordsVitiligoMedicineDermatologyJanus kinase inhibitorPopulationJanus kinaseCalcineurinInternal medicineTransplantation

Abstract

fetched live from OpenAlex

To the Editor: Vitiligo is an acquired depigmenting skin disorder due to the absence of functional melanocytes affecting up to 1% of the general population.1 Initial treatment typically involves topical corticosteroids, topical calcineurin inhibitors, and phototherapy; however, topical Janus kinase inhibitors (JAKi) are being explored as a potential treatment option. This systematic review examines the efficacy and safety of topical JAKi therapies in vitiligo.

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)0.005
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0050.006
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.026
GPT teacher head0.301
Teacher spread0.275 · 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 designSystematic review
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

Citations5
Published2022
Admission routes1
Has abstractyes

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