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Record W2078997796 · doi:10.2310/7750.2006.00051

Treatment of Mycosis Fungoides: Overview

2006· review· en· W2078997796 on OpenAlexaff
Anatoli Freiman, Denis Sasseville

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2006
Typereview
Languageen
FieldMedicine
TopicCutaneous lymphoproliferative disorders research
Canadian institutionsMcGill UniversityUniversity of Toronto
Fundersnot available
KeywordsMedicineMycosis fungoidesBexaroteneDermatologyPhotopheresisExtracorporeal PhotopheresisImiquimodCutaneous T-cell lymphomaChemotherapyPUVA therapyCarmustineLymphomaImmunologySurgeryCyclophosphamidePsoriasisTransplantationGraft-versus-host disease

Abstract

fetched live from OpenAlex

BACKGROUND: Mycosis fungoides (MF) is the most common clinicopathologic subtype of primary cutaneous T-cell lymphoma. OBJECTIVE: The therapy of MF is highlighted in this overview. RESULTS AND CONCLUSIONS: Skin-directed MF therapies include topical corticosteroids, nitrogen mustard, carmustine (BCNU), topical bexarotene gel, imiquimod cream, radiotherapy, total skin electron beam therapy, and phototherapy. Systemic therapies include extracorporeal photopheresis, interferon, oral bexarotene, denileukin diftitox, monoclonal antibodies and cytokine therapy, and other systemic chemotherapy. Finally, some investigative therapeutic modalities are presented.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.157
GPT teacher head0.414
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations10
Published2006
Admission routes1
Has abstractyes

Explore more

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