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Record W2171862413 · doi:10.3899/jrheum.100551

Biologic DMARD May Be Insufficient to Inhibit CCL20 Pathway in Rheumatoid Arthritis

2010· letter· en· W2171862413 on OpenAlexvenueno aff
Rui‐Xue Leng, Dong‐Qing Ye

Bibliographic record

VenueThe Journal of Rheumatology · 2010
Typeletter
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRheumatoid arthritisEtanerceptTocilizumabInfliximabAntirheumatic drugsCCL20Biologic AgentsAntirheumatic AgentsInternal medicineImmunologyChemokineTumor necrosis factor alphaInflammation

Abstract

fetched live from OpenAlex

To the Editor: Kawashiri, et al recently reported that biologic disease-modifying antirheumatic drugs (DMARD; i.e., infliximab, etanercept, and tocilizumab) may have therapeutic efficacy by inhibiting CCL20 production in rheumatoid synovium1. Indeed, serum CCL20 concentration in patients with rheumatoid arthritis (RA) was clearly decreased by treatment with biologic DMARD. As well, DMARD also can inhibit the production … Address correspondence to Prof. D-Q. Ye; E-mail: ydq{at}ahmu.edu.cn

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.015
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0150.013
Insufficient payload (model declined to judge)0.0030.003

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 head0.024
GPT teacher head0.271
Teacher spread0.246 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2010
Admission routes1
Has abstractyes

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