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Record W4391678945 · doi:10.1016/j.jaad.2023.12.074

Executive summary: Consensus treatment guidelines for the use of methotrexate for inflammatory skin disease in pediatric patients

2024· article· en· W4391678945 on OpenAlexafffund
Heather A. Brandling‐Bennett, Lisa M. Arkin, Yvonne E. Chiu, Adelaide A. Hebert, Jeffrey P. Callen, Leslie Castelo‐Soccio, Dominic O. Co, Kelly M. Cordoro, Megan L. Curran, Austin Dalrymple, Carsten Flohr, Ken Gordon, Diane Hanna, Alan D. Irvine, Susan Kim, A. Yasmine Kirkorian, Irene Lara‐Corrales, Jill A. Lindstrom, Amy S. Paller, Melissa Reyes, Wendy Smith Begolka, Wynnis L. Tom, Abby S. Van Voorhees, Ruth Ann Vleugels, Lara Wine Lee, Olivia M. T. Davies, Elaine C. Siegfried

Bibliographic record

VenueJournal of the American Academy of Dermatology · 2024
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersSanofi GenzymeOrtho DermatologicsLEO PharmaIpsenSanofiKyowa Hakko KirinPfizerNational Psoriasis FoundationIncyteMcGovern Medical SchoolLes Laboratories Pierre FabreDermiraSun PharmaNational Institutes of HealthRegeneron PharmaceuticalsUniversity of Texas Health Science Center at HoustonCelgeneNational Institute for Health and Care ResearchMassachusetts General HospitalValeant Pharmaceuticals InternationalEuropean CommissionPediatric Dermatology Research AllianceEli Lilly and CompanyNational Eczema AssociationAmgen
KeywordsMedicineMethotrexateConsensus conferenceDiseaseIntensive care medicineMEDLINEExecutive summaryDisease managementDermatologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

To the Editor: Methotrexate (MTX) is an inexpensive and readily available medication that is used off-label for many inflammatory skin conditions in pediatric patients, with substantial variation in dosing and monitoring. To support optimal management of pediatric inflammatory skin diseases with low-dose MTX, a 27-member expert committee convened to establish evidence-based consensus-driven guidelines.1 The following 5 major subjects were assessed: (1) indications and contraindications, (2) dosing, (3) interactions with immunizations and medications, (4) adverse effects, and (5) monitoring.

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)0.024
metaresearch head score (Gemma)0.086
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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.086
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0060.002
Research integrity0.0120.012
Insufficient payload (model declined to judge)0.0180.015

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 head0.090
GPT teacher head0.396
Teacher spread0.306 · 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

Citations2
Published2024
Admission routes2
Has abstractno

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Same venueJournal of the American Academy of DermatologySame topicAutoimmune and Inflammatory Disorders ResearchFrench-language works237,207