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Record W2099063455 · doi:10.3899/jrheum.150131

Review of the Psoriatic Arthritis Working Group at OMERACT 12: A Report from the GRAPPA 2014 Annual Meeting

2015· article· en· W2099063455 on OpenAlexaffvenue
William Tillett, Lihi Eder, Niti Goel, Maarten de Wit, Alexis Ogdie, Ana-Maria Orbai, Willemina Campbell, Oliver FitzGerald, Neil J. McHugh, Dafna D. Gladman, Vibeke Strand, Philip J. Mease

Bibliographic record

VenueThe Journal of Rheumatology · 2015
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsUniversity Health NetworkToronto Western Hospital
Fundersnot available
KeywordsPsoriatic arthritisMedicineWorking groupPhysical therapyFamily medicineMedical physicsArthritisInternal medicine

Abstract

fetched live from OpenAlex

At the 2014 annual meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA), the psoriatic arthritis (PsA) working group of OMERACT (Outcome Measures in Rheumatology) presented a review of the progress made at the OMERACT 12 meeting, held in 2014. Members of the PsA OMERACT working group presented work from the Patient Involvement in Outcome Measures for PsA initiative to improve the incorporation of patient research partners in PsA outcomes research, the results of discussions within the OMERACT breakout groups, and finally the voting results. The OMERACT 12 participants had endorsed the need to update the PsA core set according to the Filter 2.0 framework. The breakout group discussions identified potential opportunities for revising the core set, including consolidating existing redundancy within the core set, improving incorporation of the patient perspective, and including disease effects such as fatigue as a core criterion. GRAPPA members of the OMERACT working group now have a program of research to update the core set with the goal of seeking endorsement at OMERACT 13, to be held in 2016.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.293
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 teacher head, 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

Citations6
Published2015
Admission routes2
Has abstractyes

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