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Record W2094317045 · doi:10.1128/jcm.02205-14

Characterization of Multiple Cytomegalovirus Drug Resistance Mutations Detected in a Hematopoietic Stem Cell Transplant Recipient by Recombinant Phenotyping

2014· article· en· W2094317045 on OpenAlexafffund
Emilien Drouot, Jocelyne Piret, Marc Lebel, Guy Boivin

Bibliographic record

VenueJournal of Clinical Microbiology · 2014
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsDrug resistanceVirologyRecombinant DNABiologyHematopoietic stem cellStem cellHematopoietic stem cell transplantationCytomegalovirusHaematopoiesisImmunologyHerpesviridaeViral diseaseVirusMicrobiologyGeneticsGene

Abstract

fetched live from OpenAlex

Cytomegalovirus resistance to antivirals is a major problem in transplant recipients. We evaluated the impact of five mutations (A594V, L595F, and E655K in the UL97 gene and V526L and E756K in the UL54 gene), detected in a blood sample from a stem cell transplant recipient, on drug susceptibilities and replicative capacities of recombinant viruses.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.318
Teacher spread0.289 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations29
Published2014
Admission routes2
Has abstractyes

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