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Record W4318826914 · doi:10.3390/curroncol30020135

Management of Marginal Zone Lymphoma: A Canadian Perspective

2023· review· en· W4318826914 on OpenAlexaffvenueabout
Anthea Peters, Mary‐Margaret Keating, Anna Nikonova, Sarah Doucette, Anca Prica

Bibliographic record

VenueCurrent Oncology · 2023
Typereview
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreImpactUniversity of AlbertaQueen Elizabeth II Health Sciences CentreFluidigm (Canada)Dalhousie UniversityMcGill University Health Centre
Fundersnot available
KeywordsMedicineLymphomaDiseaseClinical trialLymphoplasmacytic LymphomaSplenic marginal zone lymphomaPresentation (obstetrics)PathologyInternal medicineSurgerySplenectomySpleenWaldenstrom macroglobulinemia

Abstract

fetched live from OpenAlex

Marginal zone lymphomas (MZL) are a rare, heterogenous group of lymphomas, accounting for 5-17% of indolent non-Hodgkin lymphomas in the western world. They can be further divided into three subtypes: extranodal MZL, splenic MZL, and nodal MZL. These subtypes differ in clinical presentation and behavior, which influences how they are managed. There is currently no standard of care for the treatment of MZL, owing to the difficulty in conducting phase 3 randomized trials in MZL, and the fact that there are limited data on the efficacy of therapy in individual subtypes. Treatment practices are thus largely borrowed from other indolent lymphomas and are based on patient and disease characteristics, as well as access to therapy. This review summarizes the Canadian treatment landscape for MZL and how these therapies may be sequenced in practice.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.762
Threshold uncertainty score0.474

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.202
GPT teacher head0.469
Teacher spread0.268 · 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

Citations6
Published2023
Admission routes3
Has abstractyes

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