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Lymphoma risk in systemic lupus: effects of disease activity versus treatment

2013· article· en· W2139317340 on OpenAlexafffund
Sasha Bernatsky, Rosalind Ramsey‐Goldman, Lawrence Joseph, Jean-François Boivin, Karen H. Costenbader, Murray B. Urowitz, Dafna D. Gladman, Paul R. Fortin, Ola Nived, Michelle Petri, Søren Jacobsen, Susan Manzi, Ellen M. Ginzler, David Isenberg, Anisur Rahman, Caroline Gordon, Guillermo Ruiz‐Irastorza, Edward Yelin, Sang‐Cheol Bae, Daniel J. Wallace, Christine Peschken, Mary Anne Dooley, Steven M. Edworthy, Cynthia Aranow, Diane L. Kamen, Juanita Romero‐Díaz, Anca Askanase, Torsten Witte, Susan G. Barr, Lindsey A. Criswell, Gunnar Sturfelt, Irene Blanco, Candace H. Feldman, Lene Dreyer, Neha M. Patel, Yvan St. Pierre, Ann E. Clarke

Bibliographic record

VenueAnnals of the Rheumatic Diseases · 2013
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity of CalgaryMcGill UniversityUniversité LavalRoyal Victoria Regional Health CentreMcGill University Health CentreUniversity of ManitobaToronto Western HospitalRoyal Victoria Hospital
FundersNational Center for Advancing Translational SciencesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Cancer InstituteCanadian Institutes of Health Research
KeywordsMedicineSystemic lupusSystemic lupus erythematosusLymphomaSystemic diseaseDiseaseDermatologyInternal medicineRheumatologyImmunology

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)0.004
metaresearch head score (Gemma)0.010
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 score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.033
GPT teacher head0.317
Teacher spread0.284 · 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

Citations161
Published2013
Admission routes2
Has abstractno

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