MétaCan
Menu
Back to cohort
Record W7074121379

Epstein-Barr virus infection in transplant recipients: Summary of a workshop on surveillance, prevention and treatment

2002· article· en· W7074121379 on OpenAlexaboutno aff

Bibliographic record

VenuePubMed Central · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodTSG101DiafiltrationDysgeusiaHyporeflexiaFusible alloyLiquationProteogenomics
DOInot available

Abstract

fetched live from OpenAlex

Diseases caused by the Epstein-Barr virus are of great significance among organ transplant recipients. One of these diseases, post-transplant lymphoproliferative disease, is a major complication among organ transplant recipients. Management of this entity is problematic due to the difficulties with laboratory surveillance, diagnosis, prevention and treatment. A group of Canadian and American experts was assembled to discuss these aspects of Epstein-Barr virus diseases in Canadian organ transplant recipients. This report summarizes the relevant background literature and levels of evidence in relation to the outcomes of the deliberations and recommendations by the expert panel.

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)0.012
metaresearch head score (Gemma)0.007
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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0030.003
Research integrity0.0080.007
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 head0.012
GPT teacher head0.234
Teacher spread0.222 · 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

Citations22
Published2002
Admission routes1
Has abstractyes

Explore more

Same venuePubMed CentralSame topicCell Image Analysis TechniquesFrench-language works237,207