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Record W2915016030 · doi:10.3899/jrheum.181065

OMERACT 2018 Modified Patient-reported Outcome Domain Core Set in the Life Impact Area for Adult Idiopathic Inflammatory Myopathies

2019· article· en· W2915016030 on OpenAlexaffvenue
Malin Regardt, Christopher A. Mecoli, Jin Kyun Park, Ingrid de Groot, Catherine Sarver, Merrilee Needham, Beverly Shea, Clifton O. Bingham, Ingrid E. Lundberg, Yeong Wook Song, Lisa Christopher‐Stine, Helene Alexanderson

Bibliographic record

VenueThe Journal of Rheumatology · 2019
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsUniversity of Ottawa
FundersPerron Institute for Neurological and Translational ScienceSeoul National University HospitalKarolinska Institutet
KeywordsMedicinePhysical therapyMyositisCore (optical fiber)RheumatologyDelphi methodOutcome (game theory)PolymyositisQuality of life (healthcare)Internal medicinePhysical medicine and rehabilitationArtificial intelligence

Abstract

fetched live from OpenAlex

OBJECTIVE: To present and vote on a myositis modified patient-reported outcome core domain set in the life impact area at the Outcome Measures in Rheumatology (OMERACT) 2018. METHODS: Based on results from international focus groups and Delphi surveys, a draft core set was developed. RESULTS: Domains muscle symptoms, fatigue, level of physical activity, and pain reached ≥ 70% consensus and were mandatory to assess in all trials. Domains lung, joint, and skin symptoms were mandatory in specific circumstances. This core set was endorsed by > 85% at OMERACT 2018. CONCLUSION: We propose a life impact core set for patients with idiopathic inflammatory myopathies and will proceed with instrument selections.

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)0.079
metaresearch head score (Gemma)0.120
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.079
Threshold uncertainty score0.417

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0790.120
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.038
GPT teacher head0.303
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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations46
Published2019
Admission routes2
Has abstractyes

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