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Record W2167704749 · doi:10.3899/jrheum.091048

Association of RNA Polymerase III Antibodies with Scleroderma Renal Crisis

2010· letter· en· W2167704749 on OpenAlexvenueno aff
Binh Nguyen, Shervin Assassi, Frank C. Arnett, Maureen D. Mayes

Bibliographic record

VenueThe Journal of Rheumatology · 2010
Typeletter
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsnot available
FundersNational Center for Research ResourcesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesUniversity of Texas Health Science Center at Houston
KeywordsSclerodactylyMedicineCREST SyndromeScleroderma (fungus)AutoantibodyRheumatologyInternal medicineCalcinosisDermatologySystemic sclerodermaTelangiectasiaAntibodyConnective tissue diseaseGastroenterologyPathologyDiseaseImmunologyAutoimmune disease

Abstract

fetched live from OpenAlex

To the Editor: The study by Cordullo, et al investigated the prevalence of systemic sclerosis (SSc)-related autoantibodies among SSc patients with scleroderma renal crisis (SRC) in Italy. The authors report that the majority of the SRC patients had anti-topoisomerase I (anti-topo I) antibody (30/46, 65%), whereas a minority of patients (7/46, 15%) had anti-RNA polymerase III (RNAP)1. We reviewed cases of SRC in the Scleroderma Family Registry and DNA Repository (Registry) in the USA, which consisted of 1029 patients with SSc at the time of analysis. All patients fulfilled American College of Rheumatology preliminary classification criteria2 or had at least 3 of the 5 features of CREST (calcinosis, Raynaud’s phenomenon, esophageal dysfunction, sclerodactyly, telangiectasia); the diagnosis was verified by medical record review. The Registry database included demographic features, clinical disease characteristics, including extent of skin involvement, and autoantibody … Address correspondence to Dr. Nguyen. E-mail: Binh.Nguyen{at}uth.tmc.edu

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)0.002
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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0040.002

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 head0.011
GPT teacher head0.237
Teacher spread0.226 · 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 designCase report
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

Citations41
Published2010
Admission routes1
Has abstractyes

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