Immunosuppression for interstitial lung disease in systemic sclerosis – novel insights and opportunities for translational research
Bibliographic record
Abstract
Systemic sclerosis (SSc) is a chronic inflammatory disorder characterized by a disturbance in fibroblast function culminating in the telltale skin thickening and fibrosis of visceral organs. Interstitial lung disease (ILD) is common (Steele et al. 2011) and is the leading cause of death in this disease (Steen and Medsger 2007). The immunohistopathogenesis of SSc-ILD is characterized by immune dysfunction and inflammation. Thus, immunosuppression has been hypothesized as a useful treatment for SSc-ILD. However, randomized clinical trials (RCTs) have thus far only revealed a modest effect of immunosuppression (Hoyles et al. 2006; Tashkin et al. 2006). We believe that these small observed effects are due, at least in part, to the actual design of the RCTs, in particular subject selection, which did not properly identify patients likely to respond to treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".