Bibliographic record
Abstract
This chapter describes the various ways in which the non-Hodgkin's lymphomas can involve the skin, how these diseases should be assessed, standard treatments available in 2002, and new directions in research. The goal of the session is to succinctly review recent developments in lymphoma classification and treatment as they apply to the unique aspects of lymphoma when manifest in the skin. In Section I, Dr. Eric Hsi reviews the special characteristics of the lymphomas seen when they proliferate in the skin and the application of the new World Health Organization classification system to the cutaneous lymphomas, emphasizing the unique challenges of recognizing and correctly classifying these diseases. He summarizes the evidence in favor of including the skin lymphomas in the overall lymphoma classification scheme and concludes with a practical description of the specific skin lymphoma entities. In Section II, Dr. Joseph Connors describes the current optimal treatment of the B-cell lymphomas when they present in or metastasize to the skin. Building on the classification scheme described by Dr. Hsi, Dr. Connors outlines a treatment approach based on current understanding of pathophysiology of these diseases and application of each of the effective modalities available for cutaneous lymphoma including radiation, chemotherapy, and immunotherapy. In Section III, Dr. Francine Foss concludes the session with a discussion of the different T-cell lymphomas that start in or spread to the skin concentrating on mycosis fungoides, cutaneous anaplastic large cell lymphoma and peripheral T-cell lymphoma. She includes comments on the newer anti-T-cell chemo- and immuno-therapeutics focusing on agents and techniques specific for cutaneous T-cell lymphomas.
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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) | 0.001 | 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) | 0.027 | 0.009 |
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".