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Record W2751187482 · doi:10.1097/der.0000000000000318

Contact Allergy to Hydroperoxides of Linalool and d -Limonene in a US Population

2017· article· en· W2751187482 on OpenAlexvenueno aff
Neel Nath, Beiyu Liu, Cynthia L. Green, Amber Reck Atwater

Bibliographic record

VenueDermatitis · 2017
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsLinaloolLimoneneContact allergyPatch testPatch testingMedicinePopulationAllergyAllergic contact dermatitisDermatologyFood scienceOrganic chemistryChemistryContact dermatitisImmunologyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Linalool and D-limonene are common fragrance ingredients that readily oxidize on exposure to air. The resulting hydroperoxides of linalool and D-limonene have been shown to have high frequencies of positive patch test reactions in several European and international studies. OBJECTIVE: The aim of the study was to investigate the prevalence of contact allergy to the hydroperoxides of linalool and D-limonene in a US population. METHODS: In this retrospective study, 103 patients with suspected fragrance allergy were patch tested to linalool 10% petrolatum (pet), hydroperoxides of linalool 1% pet, D-limonene 10% pet, and/or the hydroperoxides of D-limonene 0.3% pet between July 9, 2014, and October 25, 2016. CONCLUSIONS: In this study, the frequency of positive patch test reactions to the hydroperoxides of linalool is 20% (19/96), and the frequency of positive reactions to the hydroperoxides of D-limonene is 8% (7/90). These high frequencies suggest that patch testing to the hydroperoxides of linalool and limonene should be performed in all patients with suspected fragrance allergy.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.947

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 head0.015
GPT teacher head0.269
Teacher spread0.254 · 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

Citations27
Published2017
Admission routes1
Has abstractyes

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