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Record W2585797335 · doi:10.3899/jrheum.160904

Updating the Psoriatic Arthritis (PsA) Core Domain Set: A Report from the PsA Workshop at OMERACT 2016

2017· article· en· W2585797335 on OpenAlexaffvenue
Ana‐Maria Orbai, Maarten de Wit, Philip J. Mease, Kristina Callis Duffin, Musaab Elmamoun, William Tillett, Willemina Campbell, Oliver FitzGerald, Dafna D. Gladman, Niti Goel, Laure Gossec, Pil Hoejgaard, Ying Ying Leung, Chris A. Lindsay, Vibeke Strand, Désirée van der Heijde, Bev Shea, Robin Christensen, Laura C. Coates, Lihi Eder, Neil McHugh, Umut Kalyoncu, Ingrid Steinkoenig, Alexis Ogdie

Bibliographic record

VenueThe Journal of Rheumatology · 2017
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsCanada Research ChairsUniversity of TorontoToronto Western Hospital
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesProgramme Grants for Applied ResearchArthritis Center, Johns Hopkins UniversityNational Institute for Health and Care ResearchCelgenePfizerJohns Hopkins UniversityRheumatology Research Foundation
KeywordsMedicineRandomized controlled trialPsoriatic arthritisObservational studyPhysical therapyQuality of life (healthcare)Medical physicsInternal medicineDisease

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.355
metaresearch head score (Gemma)0.428
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.355
Threshold uncertainty score0.795

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3550.428
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0040.004
Science and technology studies0.0030.002
Scholarly communication0.0050.006
Open science0.0050.012
Research integrity0.0080.012
Insufficient payload (model declined to judge)0.0030.002

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 head0.031
GPT teacher head0.308
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.

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

Citations134
Published2017
Admission routes2
Has abstractyes

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