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Record W2181283091 · doi:10.1136/jclinpath-2015-203133

Primary cutaneous T-cell lymphomas: a review

2015· review· en· W2181283091 on OpenAlexaff
Konstantinos Gus Sidiropoulos, Maria Estela Martínez‐Escala, Oriol Yélamos, Joan Guitart, Michael Sidiropoulos

Bibliographic record

VenueJournal of Clinical Pathology · 2015
Typereview
Languageen
FieldMedicine
TopicCutaneous lymphoproliferative disorders research
Canadian institutionsLakeridge HealthUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsMycosis fungoidesImmunophenotypingMedicinePathologyDifferential diagnosisPathognomonicMedical diagnosisDermatologyLymphomaImmunologyDiseaseFlow cytometry

Abstract

fetched live from OpenAlex

Primary cutaneous T-cell lymphomas (CTCLs) represent a number of extranodal lymphomas arising from a malignant population of lymphocytes in the skin, with the most common type being mycosis fungoides (MF) representing half of all primary CTCLs. Despite advances in immunohistochemistry and molecular methodology, significant diagnostic challenges remain due to phenotypic overlap of primary CTCLs with several inflammatory dermatoses, secondary lymphomas, among other conditions. Clinical features such as presentation and morphology, staging, histology, immunophenotype and molecular features must be considered in detail before a diagnosis is made in order to minimise false-positive, false-negative and indeterminate diagnoses. Herein, we review primary CTCLs, including epidemiological data, a brief summary of clinical presentations, immunophenotype, molecular signatures and differential diagnoses.

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)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.226
GPT teacher head0.531
Teacher spread0.305 · 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

Citations31
Published2015
Admission routes1
Has abstractyes

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