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Record W4404169724 · doi:10.1016/j.eclinm.2024.102909

Erythema multiforme

2024· review· en· W4404169724 on OpenAlexafffundabout
Elio Kechichian, N. Dupin, David A. Wetter, Nicolás Ortonne, Scarlette Agbo-Godeau, O. Chosidow

Bibliographic record

VenueEClinicalMedicine · 2024
Typereview
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsUniversité de Sherbrooke
FundersFaculty of Medicine and Health, University of SydneyUniversité de Sherbrooke
KeywordsMedicineErythema multiformeDermatologyFamily medicine

Abstract

fetched live from OpenAlex

Erythema multiforme is an inflammatory skin and mucosal disease mainly related to infectious agents such as Herpes simplex virus, Mycoplasma pneumoniae , though it can also be "idiopathic". The characteristic skin lesions are typical or atypical acral raised target lesions. The oral mucosa can be affected, alone or in combination with other mucosal/cutaneous sites, sometimes causing extreme pain, severely impacting food intake, and warranting hospitalization. A comprehensive understanding of erythema multiforme clinical characteristics, triggering agents, and differential diagnosis including Stevens-Johnson syndrome/Toxic Epidermal Necrolysis, is crucial to conduct proper workup and management. Mycoplasma pneumoniae infection should be immediately ruled out because of the need of antibiotics. The cornerstone of management is symptomatic treatment and will be detailed in this review as well as the etiologic treatment. Lastly, the management of persistent or recurrent erythema multiforme can be challenging, especially when antivirals fail to prevent a relapse, but breakthrough treatments have been reported successful in this difficult-to-treat subset of patients. Funding The Funding was provided by the University of Sherbrooke Faculty of Medicine and Health Sciences.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.250
GPT teacher head0.539
Teacher spread0.289 · 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
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

Citations11
Published2024
Admission routes3
Has abstractyes

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