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Record W4385455848 · doi:10.3899/jrheum.2023-0506

Can Early Aggressive Treatment of Psoriasis Prevent Psoriatic Arthritis? A Debate at the GRAPPA Annual Meeting

2023· article· en· W4385455848 on OpenAlexvenueno aff
Enrique R. Soriano, Alexis Ogdie

Bibliographic record

VenueThe Journal of Rheumatology · 2023
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsoriatic arthritisPsoriasisDermatologyArthritisBiologic AgentsInternal medicineRheumatoid arthritis

Abstract

fetched live from OpenAlex

In recent years, a number of studies have examined risk factors for development of psoriatic arthritis (PsA) among patients with PsO. Most recently, 5 studies have examined the effect of biologic therapy on the development of PsA. However, the results have been mixed, with 3 studies suggesting a lower risk for PsA among those using a biologic therapy and 2 suggesting a higher risk for PsA. At the 2022 Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) meeting, Drs. Enrique Soriano and Alexis Ogdie conducted a debate to discuss the arguments for and against the use of biologic therapies in PsO for the purpose of preventing PsA.

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)0.036
metaresearch head score (Gemma)0.066
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.036
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.066
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0060.012
Open science0.0030.003
Research integrity0.0330.046
Insufficient payload (model declined to judge)0.0070.004

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 head0.014
GPT teacher head0.267
Teacher spread0.253 · 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
GenreCommentary

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

Citations8
Published2023
Admission routes1
Has abstractyes

Explore more

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