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Record W2162141232 · doi:10.1086/424447

New Developments in the Diagnosis and Management of Posttransplantation Lymphoproliferative Disorders in Solid Organ Transplant Recipients

2004· review· en· W2162141232 on OpenAlexaff
Jutta K. Preiksaitis

Bibliographic record

VenueClinical Infectious Diseases · 2004
Typereview
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineLymphoproliferative disordersMalignancyImmunologyDiseaseLymphoproliferative diseaseIntensive care medicineOrgan transplantationBroad spectrumTransplantationPathologyVirusLymphomaInternal medicine

Abstract

fetched live from OpenAlex

Posttransplantation lymphoproliferative disorders (PTLDs) have emerged as important causes of morbidity and mortality in solid organ transplant recipients. Epstein-Barr virus (EBV) plays a major pathophysiologic role in the development of many, if not most, of the highly diverse disease states, which span the spectrum from infection to malignancy, encompassed by the term "PTLD." Clinical presentation and biological behavior associated with PTLD are highly variable; patients experiencing primary EBV infection in the immediate posttransplantation period are most vulnerable. New insights into PTLD pathogenesis provide exciting opportunities for rational and targeted approaches to the diagnosis, prevention, and treatment of PTLD. This article highlights some of these developments and outlines unresolved and controversial issues in PTLD management.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.048
GPT teacher head0.395
Teacher spread0.347 · 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

Citations78
Published2004
Admission routes1
Has abstractyes

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