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Record W4405175674 · doi:10.1016/j.jdrv.2024.12.002

Outcomes of systemic janus kinase inhibitors following dupilumab for dupilumab-associated facial and neck erythema: A systematic review

2024· review· en· W4405175674 on OpenAlexaff
Rachel S. Simpson, Siddhartha Sood, Jihad Waked, Abrahim Abduelmula, Khalad Maliyar, Muskaan Sachdeva, Asfandyar Mufti, Jensen Yeung

Bibliographic record

VenueJAAD reviews. · 2024
Typereview
Languageen
FieldMedicine
TopicAutoimmune Bullous Skin Diseases
Canadian institutionsProbity Medical ResearchHealth Sciences CentreWomen's College HospitalUniversity of TorontoSunnybrook Health Science CentreWestern University
Fundersnot available
KeywordsDupilumabJanus kinaseErythemaDermatologyMedicineJanus kinase inhibitorInternal medicineAtopic dermatitisReceptor

Abstract

fetched live from OpenAlex

Dupilumab-associated facial and/or neck erythema (DA-FNE) has been reported in up to 10% of atopic dermatitis patients in clinical practice.1,2 Studies report DA-FNE may resolve with janus kinase inhibitors (JAKi). Herein, we systematically reviewed outcomes of patients with DA-FNE who switched from dupilumab to systemic JAKi.

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0040.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.036
GPT teacher head0.349
Teacher spread0.313 · 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 designSystematic review
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

Citations0
Published2024
Admission routes1
Has abstractyes

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