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Record W1965877724 · doi:10.3899/jrheum.090129

Patient-Driven Outcomes in Rheumatoid Arthritis

2009· review· en· W1965877724 on OpenAlexafffundvenue
George A. Wells

Bibliographic record

VenueJournal of Rheumatology Supplement · 2009
Typereview
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsUniversity of Ottawa
FundersBristol-Myers Squibb CanadaBristol-Myers Squibb
KeywordsMedicineRheumatoid arthritisPhysical therapyRheumatologyFeelingClinical trialDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Clinical trials evaluating therapies for the management of rheumatoid arthritis (RA) typically report disease activity using measures such as the American College of Rheumatology response criteria and Disease Activity Scores. Additional outcomes, such as feeling well and feeling less fatigue, appear to be more important to patients than traditional disease activity outcomes such as joint tenderness and stiffness. As a result, patient-driven outcomes are increasingly used in clinical trials of RA, and have been shown to provide useful information. It is proposed that factors such as Health Assessment Questionnaire scores, fatigue, sleep, and physical and mental function become part of a patient's core set of outcomes when assessing patients with RA.

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)0.007
metaresearch head score (Gemma)0.014
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: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.025
GPT teacher head0.334
Teacher spread0.309 · 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
GenreReview

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

Citations22
Published2009
Admission routes3
Has abstractyes

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