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Record W4281645582 · doi:10.7573/dic.2021-12-1

Dermatology: how to manage atopic dermatitis in patients with skin of colour

2022· review· en· W4281645582 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDrugs in Context · 2022
Typereview
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsHospital for Sick ChildrenWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineAtopic dermatitisDermatologyPresentation (obstetrics)Ethnic groupDiseaseEpidemiologySocioeconomic statusWhite (mutation)PathologyPopulationSurgeryEnvironmental health

Abstract

fetched live from OpenAlex

Atopic dermatitis (AD) is a chronic inflammatory cutaneous disease prevalent in all skin types but can differ in pathogenesis and clinical presentation. It has been documented in the literature that AD is more prevalent in Asian and Black individuals than in white individuals. Genetic variations as well as cultural and socioeconomic factors have important implications for susceptibility to AD and response to treatment in skin of colour. In this narrative review, we discuss differences in the epidemiology, pathophysiology, clinical presentation and treatment of AD in skin of colour. Additionally, we highlight the need for greater inclusivity of non-white ethnic groups in clinical trials to develop targeted treatments for diverse populations. Moreover, awareness of differences in AD presentation amongst non-white individuals may encourage patients to seek medical care earlier, leading to timely management and improved outcomes.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.940
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.283
Teacher spread0.266 · 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