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Record W1989934156 · doi:10.1097/der.0b013e31823d191f

Recommendations for a Screening Series for Allergic Contact Eyelid Dermatitis

2012· article· en· W1989934156 on OpenAlexvenueno aff
Elise M. Herro, Mohamed L. Elsaie, Rajiv I. Nijhawan, Sharon E. Jacob

Bibliographic record

VenueDermatitis · 2012
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDermatologyEyelidPatch testContact dermatitisAllergic contact dermatitisPatch testingAllergySurgeryImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Although allergic contact dermatitis of the eyelids is a common condition, limited information is available regarding the selection of patch-testing chemicals for proper evaluation. OBJECTIVE: The purpose of this analysis was to evaluate the relevance of allergens responsible for allergic eyelid dermatitis among a series of patch-tested patients attending our clinic at the University of Miami and compare these results to published studies in the literature. METHODS: Data were retrospectively reviewed for eyelid-only dermatitis from clinically relevant patch-test evaluations performed between December 2004 and January 2007. RESULTS: Formaldehyde was the most frequently encountered antigen, accounting for 45.83% (11/24) of the cases, followed by nickel 33.33% (8/24) and balsam of Peru (Myroxylon pereirae) 29.17% (7/24). In addition, not only did we find a higher prevalence of certain allergens when compared with other studies, but we identified several relevant allergens not previously reported at other referral centers. CONCLUSIONS: The allergens found to be relevant in eyelid dermatitis vary among different regions. These data may help contribute to generating a standard screening tool to improve the detection and management of these cases.

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 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.771
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.042
GPT teacher head0.301
Teacher spread0.259 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations23
Published2012
Admission routes1
Has abstractyes

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