Bibliometric analysis of childhood-onset systemic lupus erythematosus from 2000 to 2022
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.127 | 0.155 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".