Interleukin 6 in Systemic Sclerosis and Potential Implications for Targeted Therapy
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to review the potential importance of interleukin 6 (IL-6) in systemic sclerosis (SSc). METHODS: PubMed and Scopus databases and American College of Rheumatology (from 2009-10) and European League Against Rheumatism abstracts (2009-11) were searched using keywords "scleroderma; SSc; cytokines; interleukins; interleukin 6" and publications were excluded if not pertaining to IL-6 in SSc. Data were extracted from selected articles to construct a cell interaction model of the effects of IL-6 in SSc. RESULTS: A total of 416 reports were found (PubMed, n = 82; Scopus, n = 331; 3 abstracts); 372 were excluded (irrelevant) leaving 41 publications and 3 abstracts (39 from PubMed, 18 from Scopus; but 16 were repeated from PubMed search), where 40 suggested IL-6 was important in SSc and 4 did not. Effects of IL-6 in SSc were summarized schematically. CONCLUSION: Of the 44 publications, 40 suggested that IL-6 may be important in SSc, allowing for a conceptual framework within SSc including effects on macrophages, fibroblasts, plasma cells, monocytes, and extracellular matrix.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".