Osteolytic Lesion in PAPA Syndrome Responding to Anti-interleukin 1 Treatment
Bibliographic record
Abstract
To the Editor: Born from an uneventful pregnancy and in complete well-being, a girl at the age of 18 months presented arthritis of the left knee associated to low-grade fever, leukocytosis, and increased inflammatory markers. The arthrocentesis revealed turbid fluid with a negative culture. The girl was treated with intravenous antibiotic therapy with a temporary partial improvement, but pain and swelling of the left knee recurred and worsened in the subsequent months. Pain at the lower left limb was also referred without signs of arthritis at the ankle. Radiograph of the lower limbs was performed revealing the presence of an osteolytic area of about 2.3 cm × 0.7 cm with periosteal apposition in the distal diaphysis of the left tibia. Bone scintigraphy showed a metabolic hyperactivity in the same area only. Bone biopsy was negative for malignancy, histiocytosis, or tuberculosis while revealing the presence of an inflammatory infiltrate with neutrophils, macrophages, and monocytes, consistent with a diagnosis of chronic osteomyelitis. Nonsteroidal antiinflammatory drug treatment was started, with poor response. Bone marrow … Address correspondence to Dr. Marco Gattorno, MD, UO Pediatria 2, Istituto Giannina Gaslini, Largo Giannina Gaslini 5, 16147, Genoa, Italy. E-mail: marcogattorno{at}ospedale-gaslini.ge.it
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.004 |
| 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".