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Record W2395559579 · doi:10.1097/der.0000000000000111

Polysensitization and Individual Susceptibility to Allergic Contact Dermatitis

2015· article· en· W2395559579 on OpenAlexvenueno aff
Amy L. Gosnell, Brian Schmotzer, Susan Nedorost

Bibliographic record

VenueDermatitis · 2015
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsAtopic dermatitisMedicineContact dermatitisDermatologyAllergic contact dermatitisSensitizationAllergyImmunologySkin reaction

Abstract

fetched live from OpenAlex

BACKGROUND: Patients with allergic contact dermatitis to 1 antigen have been shown to be at increased risk of developing delayed type hypersensitivity reactions to additional antigens. Both environmental and genetic factors likely influence the risk of sensitization. OBJECTIVE: The aim of this study was to determine whether polysensitization occurs at a higher frequency than would be expected based on chance and whether polysensitization occurs more often in subsets of patients with hand involvement and atopic dermatitis. METHODS: From a database of patch test results from a single practitioner, the probability of having positive reactions to 3 or more unrelated allergens was calculated under the assumption that positive reactions are independent and compared with the observed proportion having positive reactions to 3 or more unrelated allergens. The analysis was repeated excluding patients with leg involvement as a proxy for venous insufficiency dermatitis. The proportion of patients from the polysensitized and nonpolysensitized cohorts with either hand involvement or a history of atopic dermatitis was also calculated. CONCLUSIONS: Polysensitization occurs more often than expected based on chance. Polysensitized patients were more likely to have hand dermatitis. Atopic dermatitis was not significantly associated with polysensitization in this analysis. Polysensitized individuals may represent a phenotype with increased genetic susceptibility to sensitization.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.869

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 communication0.0000.000
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 head0.032
GPT teacher head0.269
Teacher spread0.238 · 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.

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

Citations18
Published2015
Admission routes1
Has abstractyes

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