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Record W2796280724 · doi:10.1097/der.0000000000000362

The Medical Necessity of Comprehensive Patch Testing

2018· review· en· W2796280724 on OpenAlexvenueno aff
Tian Hao Zhu, Raagini Suresh, Erin M. Warshaw, Pamela L. Scheinman, Christen M. Mowad, Nina Botto, Bruce A. Brod, James S. Taylor, Amber Reck Atwater, Kalman L. Watsky, Peter C. Schalock, Brian C Machler, Stephen E. Helms, Sharon E. Jacob, Jenny E. Murase

Bibliographic record

VenueDermatitis · 2018
Typereview
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDermatologyPatch testingAllergenAllergic contact dermatitisContact dermatitisCosmeticsPatch testAllergyImmunologyPathology

Abstract

fetched live from OpenAlex

Allergic contact dermatitis is associated with significant disease and economic burden in the United States. To properly manage allergic contact dermatitis, it is important to accurately identify the substance(s) implicated in the dermatitis to prevent disease recurrence. The commercially available T.R.U.E Test (36 allergens) screening panel has been reported to have a conservative hypothetical allergen detection rate of 66.0%, at most. Importantly, these calculations are based on the 78% of patients who had clinically relevant reactions to allergens present on the North American Contact Dermatitis Group screening series (70 allergens), without the use of supplemental allergens. Testing with supplemental allergens beyond a screening series can more fully evaluate an individual's environmental and occupational exposure, which may significantly increase diagnostic accuracy. Comprehensive patch testing with additional allergens in sunscreens, cosmetics, and fragrances, for example, may increase the diagnostic yield as well as the likelihood of achieving a cure if the dermatitis is chronic and recalcitrant.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.927
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.069
GPT teacher head0.344
Teacher spread0.275 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations25
Published2018
Admission routes1
Has abstractyes

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