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2013 classification criteria for systemic sclerosis: an American college of rheumatology/European league against rheumatism collaborative initiative

2013· article· en· W2164096595 on OpenAlexafffund
F.H.J. van den Hoogen, Dinesh Khanna, Jaap Fransen, Sindhu R. Johnson, Murray Baron, Alan Tyndall, Marco Matucci‐Cerinic, Raymond P. Naden, Thomas A. Medsger, Patrícia Carreira, Gabriela Riemekasten, Philip J. Clements, Christopher P. Denton, Oliver Distler, Yannick Allanore, Daniel E. Furst, Armando Gabrielli, Maureen D. Mayes, Jacob M. van Laar, James R. Seibold, László Czirják, Virginia Steen, Murat İnanç, Otylia Kowal‐Bielecka, Ulf Müller‐Ladner, Gabriele Valentini, Douglas J. Veale, Madelon C Vonk, Ulrich A. Walker, David H. Collier, Mary Ellen Csuka, Barri J. Fessler, Serena Guiducci, Ariane L. Herrick, Vivien Hsu, Sergio A. Jiménez, Bashar Kahaleh, Peter A. Merkel, S. Sierakowski, Richard M. Silver, Robert W. Simms, John Varga, Janet Pope

Bibliographic record

VenueAnnals of the Rheumatic Diseases · 2013
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsWestern UniversityMcGill UniversityToronto Western HospitalJewish General HospitalSt Joseph's Health CareUniversity of TorontoMount Sinai Hospital
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesCanadian Institutes of Health Research
KeywordsMedicineRheumatismRheumatologyInternal medicineScleroderma (fungus)DermatologyPathology

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)0.005
metaresearch head score (Gemma)0.011
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0100.007
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0030.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.004

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 head0.081
GPT teacher head0.320
Teacher spread0.239 · 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
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

Citations2,876
Published2013
Admission routes2
Has abstractno

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