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Record W1995695847 · doi:10.3899/jrheum.101102

The Spondyloarthritis Research Consortium of Canada Registry for Spondyloarthritis

2011· article· en· W1995695847 on OpenAlexafffundvenueabout
Dafna D. Gladman, Proton Rahman, Richard J. Cook, Hua Shen, Michel Zummer, G. T. D. Thomson, Bindu Nair, Sherry Rohekar, Renise Ayearst, Robert D. Inman, Walter P. Maksymowych

Bibliographic record

VenueThe Journal of Rheumatology · 2011
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health ResearchArthritis Society
KeywordsMedicineDiseaseQuality of life (healthcare)Ankylosing spondylitisAxial spondyloarthritisArthritisPhysical therapyFamily medicineGerontologyInternal medicine

Abstract

fetched live from OpenAlex

The Spondyloarthritis Research Consortium of Cananda (SPARCC) is a transdiscliplinary research network of investigators interested in spondyloarthritis. The group has been supported by a new research initiative by The Arthritis Society. SPARCC aims to address the genetic basis of susceptibility of the disease and develop and validate clinical and imaging outcomes to assess disease activity and structural damage over time, the response to therapy, and the clinical burden of illness in terms of quality of life and disability. The first step was to develop a database that would allow ascertainment of phenotype for genetic studies, as well as accurate and detailed longitudinal information for disease expression and outcome studies. This article describes the SPARCC database and outlines difficulties and possible solutions for maintaining such a database.

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.016
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.004

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 head0.050
GPT teacher head0.306
Teacher spread0.256 · 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 designObservational
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

Citations21
Published2011
Admission routes4
Has abstractyes

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