Gaining the Upper Hand on Systemic Sclerosis Digital Ulcers
Bibliographic record
Abstract
Vasculopathy of the small blood vessels is one of the cardinal features of systemic sclerosis (SSc). The anatomical alterations of the microcirculation and small blood vessels associated with Raynaud phenomenon, the most common vascular manifestation of SSc, in combination with endothelial dysregulation and altered coagulation and fibrinolysis can lead to digital ulcers (DU)1,2. DU are a severe manifestation of SSc-associated vasculopathy, affecting up to half of patients with SSc, and are associated with a more fulminant SSc disease course1,3. Current treatment options for DU remain inadequate, and DU continue to cause a large degree of pain and disability for patients with SSc1. Two randomized controlled trials (RCT) have supported the use of intravenous iloprost in the treatment of active DU4,5, and current treatment recommendations suggest that phosphodiesterase 5 inhibitors may be efficacious in the treatment of DU6. The success of endothelin receptor antagonists (ERA) in the treatment of pulmonary arterial hypertension, another severe vasculopathic manifestation of SSc, triggered interest in their use for the treatment of DU. The RAPIDS-1 and RAPIDS-2 RCT evaluated the effect of bosentan on DU prevention and healing. In both studies, bosentan reduced the number of new DU, and the treatment effects appeared to be most pronounced in those patients with > 4 DU at baseline7,8. In these trials, the diagnosis of new DU and assessment of DU healing were … Address correspondence to Assoc. Prof. M. Nikpour, Departments of Rheumatology and Medicine, The University of Melbourne at St Vincent’s, Hospital (Melbourne), 41 Victoria Parade, Fitzroy VIC, 3065, Australia. E-mail: m.nikpour{at}unimelb.edu.au
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.166 | 0.024 |
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".