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Record W4410404263 · doi:10.3899/jrheum.2025-0330

The Road to a New Horizon in Psoriatic Arthritis

2025· article· en· W4410404263 on OpenAlexafffundvenue
Dafna D. Gladman

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsUniversity Health Network
FundersCanadian Institutes of Health ResearchKrembil FoundationArthritis SocietyNational Psoriasis Foundation
KeywordsMedicinePsoriatic arthritisPsoriasisDiseaseArthritisQuality of life (healthcare)PopulationIntensive care medicineDermatologyInternal medicineGerontologyEnvironmental health

Abstract

fetched live from OpenAlex

Although arthritis among patients with psoriasis was described in the 19th century, the question of whether there was a specific form of arthritis associated with psoriasis was not raised until the middle of the 20th century. It was only after the seminal work of Moll and Wright that psoriatic arthritis (PsA) was recognized as a distinct entity. There was little interest in studying the disease until the second half of the 20th century. Initially, it was thought to be a mild disease, but subsequent studies over the past 50 years demonstrated that it was a severe disease, occurring much more frequently than first described and leading to progressive joint damage, disability, reduced quality of life and function, and an increased mortality risk. Comorbidities were found to be more common in this patient population, possibly contributing to the poor outcomes. Advances of new therapies and better assessment tools have led to improvement in the outcomes of patients with PsA. However, there are still unmet needs that will require addressing in the next few years to improve the lives of patients with this disease.

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)0.014
metaresearch head score (Gemma)0.020
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 score0.014
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0020.008
Scholarly communication0.0050.014
Open science0.0010.004
Research integrity0.0090.017
Insufficient payload (model declined to judge)0.0100.004

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 head0.009
GPT teacher head0.275
Teacher spread0.265 · 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

Citations4
Published2025
Admission routes3
Has abstractyes

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