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Record W4237213448 · doi:10.1097/der.0000000000000025

Benzophenones

2014· article· en· W4237213448 on OpenAlexvenueno aff
Ashley R. Heurung, Srihari Raju, Erin M. Warshaw

Bibliographic record

VenueDermatitis · 2014
Typearticle
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDermatologyCosmeticsContact dermatitisAllergic contact dermatitisAllergyAllergenContact allergyAnaphylaxisImmunologyPathology

Abstract

fetched live from OpenAlex

Benzophenones are ultraviolet light filters that have been documented to cause a myriad of adverse cutaneous reactions, including contact and photocontact dermatitis, contact and photocontact urticaria, and anaphylaxis. In recent years, they have become particularly well known for their ability to induce allergy and photoallergy. Topical sunscreens and other cosmetics are the sources of these allergens in most patients, but reports of reactions secondary to use of industrial products also exist. Benzophenones as a group have been named the American Contact Dermatitis Society's Allergen of the Year for 2014 to raise awareness of both allergy and photoallergy to these ubiquitous agents.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0480.016

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 head0.010
GPT teacher head0.242
Teacher spread0.231 · 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 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

Citations76
Published2014
Admission routes1
Has abstractyes

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