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Record W4391650165 · doi:10.1177/12034754231223699

Real-World Experience of Vitiligo Patients: A Retrospective Chart Review

2024· article· en· W4391650165 on OpenAlexaffabout
Chelsea Obeng-Asumeng, Fabian Rodríguez-Bolaños, Melinda Gooderham

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicmelanin and skin pigmentation
Canadian institutionsSKiN HealthQueen's UniversityUniversity of TorontoTrent University
Fundersnot available
KeywordsMedicineVitiligoRetrospective cohort studyMedical recordDermatologyChartPresentation (obstetrics)PopulationPediatricsSurgeryEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Vitiligo is a common depigmenting skin disorder with an estimated prevalence of 0.5% to 2% worldwide. OBJECTIVE: We conducted a study to characterize the presentation of vitiligo in community dermatology clinic setting in Ontario, Canada. METHODS: A retrospective cross-sectional study was performed through an electronic chart review at a community dermatology clinic with 2 sites in Ontario, Canada. RESULTS: We found a male to female ratio of 1:1.3. The average age at the time of assessment was 40.8 years (ranging from 7 to 75 years). Sixteen percent of the patients were children (less than 18 years of age). Hands were the most common location for vitiligo (55.8%). CONCLUSIONS: Our findings are in keeping with previously described epidemiologic data. To our knowledge, this is the first Canadian study looking at the population in a community setting.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.468

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.299
Teacher spread0.284 · 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 designObservational
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

Citations5
Published2024
Admission routes2
Has abstractyes

Explore more

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