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Record W1767114213 · doi:10.3899/jrheum.141470

Anti-Jo1 Antibody in Polymyositis/dermatomyositis Is Still Closely Associated with Lung rather than Joints

2015· letter· en· W1767114213 on OpenAlexvenueno aff
La‐He Jearn, Think‐You Kim

Bibliographic record

VenueThe Journal of Rheumatology · 2015
Typeletter
Languageen
FieldMedicine
TopicInflammatory Myopathies and Dermatomyositis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePolymyositisDermatomyositisArthritisInterstitial lung diseaseContext (archaeology)MyositisInflammatory myopathyInternal medicineDermatologyLung

Abstract

fetched live from OpenAlex

To the Editor: We read with interest the paper by Klein, et al 1 containing detailed data about arthritis in patients with idiopathic inflammatory myopathy (IIM). The authors reported that arthritis was a common feature of IIM that appeared not only at the onset of disease, but also might precede muscular manifestation and occur at any time. Especially noteworthy, 27 out of 29 anti-Jo1–positive patients (93.1%) had arthritis, and this finding led authors to confirm a strong association between arthritis and anti-Jo1. Traditionally, anti-Jo1 is known to be associated with interstitial pulmonary disease and polymyositis (PM)/dermatomyositis (DM), often manifesting the pulmonary symptom. It had occasionally been reported in arthritis in patients with PM/DM, but there were not enough occurrences to treat the relationship with anti-Jo1. In that context, the authors’ 93.1% was an exceptional result considerably distinguished from previous data. We investigated … Address correspondence to Dr. T.Y. Kim, Division of Diagnostic Immunology/Department of Laboratory Medicine, Hanyang University Medical Center, 222 Wangsimni-ro, Seongdong-gu, Seoul, 133-792, Republic of Korea. E-mail: tykim{at}hanyang.ac.kr

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0120.011
Insufficient payload (model declined to judge)0.0020.002

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 head0.012
GPT teacher head0.262
Teacher spread0.250 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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