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Record W2898796149 · doi:10.1080/21645515.2018.1543525

Epstein-Barr virus (EBV) status in colorectal cancer: a mini review

2018· review· de· W2898796149 on OpenAlexaff
Shahinaz Bedri, Ali A. Sultan, Moussa Alkhalaf, Ala‐Eddin Al Moustafa, Semir Vranić

Bibliographic record

VenueHuman Vaccines & Immunotherapeutics · 2018
Typereview
Languagede
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsColorectal cancerEpstein–Barr virusVirusMedicineEpidemiologyImmunologyCancerColorectal adenomaBiologyOncologyVirologyInternal medicine

Abstract

fetched live from OpenAlex

Epstein-Barr virus (EBV) is a well-characterized oncovirus, associated with several malignancies. The complex and heterogeneous nature of colorectal cancer (CRC) has led to many epidemiological causal associations with CRC. However, a direct causal link between microbial infections and CRC has not been established yet. Our review indicates that the current evidence for the presence and role in EBV in CRC is insufficient and contradictory. The design of the analyzed studies, sample size as well as methodology used for EBV detection varied markedly and consequently may not lead to meaningful conclusions. The presence of EBV in other colorectal tumors (lymphomas, smooth muscle tumors) is in line with their status at other anatomic locations and may have therapeutic implications with EBV-specific vaccines. On the other hand, studies exploring EBV in colorectal adenoma-carcinoma sequence and its molecular genetic characteristics are largely missing and may significantly contribute to a better understanding of the role of EBV in CRC.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.805
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.042
GPT teacher head0.353
Teacher spread0.311 · 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; both teacher heads agree on what is shown here.

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

Citations54
Published2018
Admission routes1
Has abstractyes

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