Fever, recurrent ulcers, pustules, and arterial aneurysm in an adolescent male
Bibliographic record
Abstract
A 16-year-old male of Chinese and Polish descent presented to the hospital with 3–4 weeks of fever, night sweats, and weight loss. Review of systems revealed 5–6 episodes of recurrent painful oral ulcers for a year and two penile ulcers over 10 months. A focused history noted painful erythematous nodules on the lower legs that started 6 months ago with spontaneous resolution over one month (Figure 1). ... Physical examination revealed buccal ulcers (Figure 2), a small ulcer on the glans penis, and pustules over the knee, shoulders, chest, and forehead (Figure 3). He also had a pulsatile mass over the right upper leg associated with pain and tenderness. Doppler ultrasound and MRI with contrast revealed a right common iliac artery aneurysm. During hospitalization, pustules developed at intravenous (IV) sites, resolving in days (Figure 4). ... ... ... The patient met the paediatric Behçet’s disease criteria (PEDBD) and the International Criteria for Behçet’s Disease (ICBD), exhibiting recurrent oral ulcerations, skin involvement and vascular complications (1,2).The patient scored seven points according to the ICBD, exceeding the diagnostic threshold of four. He did not have any eye or neurological involvement. He had a positive pathergy test.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".