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GRAPPA-OMERACT initiative to standardise outcomes in psoriatic arthritis clinical trials and longitudinal observational studies

2017· letter· en· W2737567623 on OpenAlexaff
William Tillett, Ana‐Maria Orbai, Alexis Ogdie, Ying Ying Leung, Vibeke Strand, Dafna D. Gladman, Philip J. Mease, Laura C. Coates

Bibliographic record

VenueAnnals of the Rheumatic Diseases · 2017
Typeletter
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsToronto Western HospitalUniversity Health Network
FundersNational Institute for Health and Care Research
KeywordsDactylitisMedicinePsoriatic arthritisEnthesitisObservational studyClinical trialPhysical therapyMedical physicsDiseaseInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.119
metaresearch head score (Gemma)0.446
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score0.628

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1190.446
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0020.003
Science and technology studies0.0020.004
Scholarly communication0.0080.005
Open science0.0030.005
Research integrity0.0360.036
Insufficient payload (model declined to judge)0.0040.006

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 head0.531
GPT teacher head0.529
Teacher spread0.002 · 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 designNot applicable
DomainMethods
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

Citations21
Published2017
Admission routes1
Has abstractno

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