Cutaneous and subcutaneous lymphomas in children
Bibliographic record
Abstract
Introduction Classification of cutaneous lymphomas The skin is the second most common site of extranodal lymphoma after the gastrointestinal tract [1]. The term primary cutaneous lymphoma refers to cutaneous lymphomas that present in the skin with no evidence of extracutaneous disease at the time of diagnosis [2]. This chapter adopts the 2005 WHO/EORTC classification (Table 26.1) for cutaneous lymphomas [2, 3]. Prior to its publication, the two classification schemes most widely used were the 2001 World Health Organization (WHO) classification [4] and the 1997 European Organization for the Research and Treatment of Cancer (EORTC) classification [5]. The 2005 WHO/EORTC classification is a consensus system based on the premise that primary cutaneous lymphomas often have a completely different clinical behavior and prognosis from histologically similar nodal lymphomas: therefore, they require different management strategies and treatment. This new classification is validated by clinical follow-up data on 1905 patients from the Dutch and Austrian registries for primary cutaneous lymphomas [6]. Epidemiology in the pediatric age group Primary cutaneous lymphomas are extremely rare, with an incidence of approximately 0.36 per 100 000 [7] persons per year. Cutaneous T-cell lymphomas (CTCLs) account for approximately 75% of all cutaneous lymphomas in Europe [5] and >90% in North America. Although typically considered a disease of adulthood (approximately 75% of patients are diagnosed after 50 years of age [8]), pediatric cases make up from 4 to 11% of CTCL cases, and many adult patients report initial onset in childhood [8–10].
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".