MétaCan
Menu
Back to cohort
Record W2781647923 · doi:10.1111/pin.12621

Gastrointestinal follicular lymphoma: Current knowledge and future challenges

2018· review· en· W2781647923 on OpenAlexaff
Katsuyoshi Takata, Tomoko Miyata‐Takata, Yasuharu Sato, Masaya Iwamuro, Hiroyuki Okada, Akira Tari, Tadashi Yoshino

Bibliographic record

VenuePathology International · 2018
Typereview
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsSpinal Cord Injury BCBC Cancer Agency
Fundersnot available
KeywordsPathologyDuodenumLymphomaFollicular lymphomaGastrointestinal tractCD99ImmunophenotypingMedicineBiologyImmunohistochemistryInternal medicineAntigenImmunology

Abstract

fetched live from OpenAlex

The gastrointestinal (GI) tract is the most commonly involved site of extranodal follicular lymphoma (FL). GI-FL shows very indolent clinical behavior and localized at GI tract without any progression or transformation compared to nodal FL. The most frequently involved site of the GI tract was the duodenum followed by the jejunum and ileum, and only 15% of FL arising in the second part of the duodenum were localized there without scattered very small daughter lesions in other GI tract examined by double-balloon endoscopy. The typical macroscopic appearance of GI-FL was multiple white nodules. Microscopically, neoplastic cells were small- to medium-sized lymphoid cells and formed neoplastic follicles. Most of the cases (>95%) were histologically Grade 1 to 2 (low grade). Several pathological and molecular characteristics were seen in GI-FL (especially duodenal FL) compared with nodal FL: immunoglobulin heavy chain deviation to VH4 and VH5; memory B-cell immunophenotype; and molecular features shared by mucosa-associated lymphoid tissue lymphoma. Considering the pathological and molecular uniqueness of this disease, GI-FL should be separately managed from nodal FL.

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)0.003
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0020.003
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 head0.057
GPT teacher head0.365
Teacher spread0.308 · 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

Citations40
Published2018
Admission routes1
Has abstractyes

Explore more

Same venuePathology InternationalSame topicLymphoma Diagnosis and TreatmentFrench-language works237,207