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Record W1947240820

Acneiform facial eruptions: a problem for young women.

2005· article· en· W1947240820 on OpenAlexaff
Melody J Cheung, Muba Taher, Gilles J. Lauzon

Bibliographic record

VenuePubMed · 2005
Typearticle
Languageen
FieldMedicine
TopicAcne and Rosacea Treatments and Effects
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRosaceaMedicineDermatologyAcneFolliculitisPapulopustular
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To summarize clinical recognition and current management strategies for four types of acneiform facial eruptions common in young women: acne vulgaris, rosacea, folliculitis, and perioral dermatitis. QUALITY OF EVIDENCE: Many randomized controlled trials (level I evidence) have studied treatments for acne vulgaris over the years. Treatment recommendations for rosacea, folliculitis, and perioral dermatitis are based predominantly on comparison and open-label studies (level II evidence) as well as expert opinion and consensus statements (level III evidence). MAIN MESSAGE: Young women with acneiform facial eruptions often present in primary care. Differentiating between morphologically similar conditions is often difficult. Accurate diagnosis is important because treatment approaches are different for each disease. CONCLUSION: Careful visual assessment with an appreciation for subtle morphologic differences and associated clinical factors will help with diagnosis of these common acneiform facial eruptions and lead to appropriate management.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.020
GPT teacher head0.253
Teacher spread0.233 · 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
Published2005
Admission routes1
Has abstractyes

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