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Record W4392885723 · doi:10.1002/ski2.359

Clinical Course, Treatment and Management of Generalised Pustular Psoriasis from a United Kingdom Extension of a Global Delphi Panel

2024· article· en· W4392885723 on OpenAlexaff
G Becher, A. David Burden, Andrew Pink, Maria Zacharioudaki, Richard B. Warren

Bibliographic record

VenueSkin Health and Disease · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsInstitute of Infection and Immunity
FundersBoehringer Ingelheim
KeywordsDelphi methodDelphiMedicinePsoriasisDiseaseDisease managementFamily medicineDermatologyPathologyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

This article presents the results of the UK extension of a previously conducted global Delphi panel on generalised pustular psoriasis (GPP). Five UK based dermatologists experienced in GPP management have expressed their level of agreement on 101 questionnaire statements addressing four aspects of GPP: clinical course and flare definition, diagnosis, treatment goals, and holistic management. Consensus was achieved for 89 of 101 statements (88%). Disagreement was detected on issues around the prognostic value of age, QoL assessment tools and the nature of comorbidities associated with GPP. Overall, the panelists corroborated the results of the global study and confirmed that the clinical algorithm derived from the global study is in accordance with the UK clinical practice.

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)0.032
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.077
GPT teacher head0.354
Teacher spread0.277 · 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 designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

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