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Record W4366609951 · doi:10.1136/ard-2022-223808

Machine learning identifies clusters of longitudinal autoantibody profiles predictive of systemic lupus erythematosus disease outcomes

2023· article· en· W4366609951 on OpenAlexafffund
May Y. Choi, Irene A. Chen, Ann E. Clarke, Marvin J. Fritzler, Katherine A Buhler, Murray B. Urowitz, John G. Hanly, Yvan St‐Pierre, Caroline Gordon, Sang‐Cheol Bae, Juanita Romero‐Díaz, Jorge Sánchez‐Guerrero, Sasha Bernatsky, Daniel J. Wallace, David Isenberg, Anisur Rahman, Joan T. Merrill, Paul R. Fortin, Dafna D. Gladman, Ian N Bruce, Michelle Petri, Ellen M. Ginzler, Mary Anne Dooley, Rosalind Ramsey‐Goldman, Susan Manzi, Andreas Jönsen, Graciela S. Alarcón, Ronald van Vollenhoven, Cynthia Aranow, Meggan Mackay, Guillermo Ruiz‐Irastorza, Sam Lim, Murat İnanç, Kenneth Kalunian, Søren Jacobsen, Christine Peschken, Diane L. Kamen, Anca Askanase, Jill P. Buyon, David Sontag, Karen H. Costenbader

Bibliographic record

VenueAnnals of the Rheumatic Diseases · 2023
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsMount Sinai HospitalMcGill University Health CentreUniversity Health NetworkUniversity of TorontoDalhousie UniversityUniversity of ManitobaToronto Western HospitalUniversité LavalQueen Elizabeth II Health Sciences CentreUniversity of Calgary
FundersNational Center for Research ResourcesLupus Foundation of AmericaCanada Research ChairsCanadian Institutes of Health ResearchLUPUS UKNational Institute for Health and Care ResearchVersus ArthritisNational Institute of Arthritis and Musculoskeletal and Skin DiseasesArthritis SocietySandwell and West Birmingham Hospitals NHS TrustNational Center for Advancing Translational SciencesWellcome TrustNational Research Foundation of Korea
KeywordsMedicineAutoantibodyDiseaseImmunologySystemic diseaseSystemic lupus erythematosusInternal medicineAntibody

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)0.002
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.338
Teacher spread0.293 · 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

Citations81
Published2023
Admission routes2
Has abstractno

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