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Neuropsychiatric events in systemic lupus erythematosus: a longitudinal analysis of outcomes in an international inception cohort using a multistate model approach

2020· article· en· W2999809542 on OpenAlexafffund
John G. Hanly, Murray B. Urowitz, Caroline Gordon, Sang‐Cheol Bae, Juanita Romero‐Díaz, Jorge Sánchez‐Guerrero, Sasha Bernatsky, Ann E. Clarke, 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, Vernon T. Farewell

Bibliographic record

VenueAnnals of the Rheumatic Diseases · 2020
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity of CalgaryMcGill UniversityUniversity of ManitobaToronto Western HospitalUniversity of TorontoUniversité LavalQueen Elizabeth II Health Sciences Centre
FundersNational Center for Research ResourcesNational Institutes of HealthNovo NordiskNational Institute for Health and Care ResearchCanadian Institutes of Health ResearchLupus Research AllianceNational Institute of Arthritis and Musculoskeletal and Skin DiseasesVersus ArthritisNational Center for Chronic Disease Prevention and Health PromotionUniversity of CalgaryWellcome TrustArthritis SocietyGigtforeningenJohns Hopkins UniversityEusko JaurlaritzaUniversité Laval
KeywordsMedicineCohortCohort studySystemic lupus erythematosusInternal medicineDisease

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.099
GPT teacher head0.372
Teacher spread0.273 · 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 teacher head, 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

Citations77
Published2020
Admission routes2
Has abstractno

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