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Record W4391484749 · doi:10.1177/09612033241230586

Bibliometric analysis of childhood-onset systemic lupus erythematosus from 2000 to 2022

2024· article· en· W4391484749 on OpenAlexaboutno aff
Hao Yu, Xintong Xie, Guangliang Wei, Huidong Chen, Xue Zhang, Youxian He, Mengxiang Li, Chengsong He, Yue He, Jie Chen

Bibliographic record

VenueLupus · 2024
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLupus nephritisSystemic lupus erythematosusDiseasePathology

Abstract

fetched live from OpenAlex

Background Systemic lupus erythematosus (SLE) is a chronic, multisystem autoimmune disorder. When SLE occurs in individuals under the age of 18, it is referred to as childhood-onset SLE (cSLE). Currently, there is a dearth of bibliometric research pertaining to cSLE. Method Relevant studies in the field of cSLE from 2000 to 2022 were screened from the Web of Science Core Collection (WoSCC). CiteSpace and VOSviewer software were used to visualize the annual publications, countries, institutions, authors, journals, keywords, and references, after which the authors conducted the scientific analysis. Results A total of 2857 articles were included in this study, and the number of articles published in the past 20 years showed an overall upwards trend. The most prolific countries are the United States, China, and Brazil; however, the United States, Canada, and the United Kingdom are clearly superior in terms of literary influence, and there is more cooperation between them and their institutions. LUPUS ( n = 389) contributed the most to the variance. Brunner, HI’s contribution in the field of cSLE is outstanding. The words related to ‘lupus nephritis’ and ‘antibodies’ are important words reflected in the keyword network diagram. The keywords included ‘evidence-based recommendation’, ‘validation’, ‘diagnosis’ and ‘adult’ from 2019, and ‘continuous bursts’ to the present. Conclusion This study examined the research status of cSLE patients, discussed and analysed the research hotspots and trends in this field, and provided a reference for further research in this field to promote the development of cSLE research.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Bibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesBibliometrics, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.1290.266
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.305
Teacher spread0.286 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2024
Admission routes1
Has abstractyes

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