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Record W2419820409 · doi:10.1177/135965350601100315

Oligonucleotide-Based Therapeutic Options against Hepatitis C Virus Infection

2006· article· en· W2419820409 on OpenAlexaff
Janie B. Trépanier, Jerome E. Tanner, Caroline Alfieri

Bibliographic record

VenueAntiviral Therapy · 2006
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsRibozymeHepatitis C virusVirologyOligonucleotideBiologyComputational biologyHepatitis CVirusRNADNAGeneticsGene

Abstract

fetched live from OpenAlex

The hepatitis C virus (HCV) is the cause of a silent pandemic that, due to the chronic nature of the disease and the absence of curative therapy, continues to claim an ever-increasing number of lives. Current antiviral regimens have proven largely unsatisfactory for patients with HCV drug-resistant genotypes. It is therefore important to explore alternative therapeutic stratagems whose mode of action allows them to bypass viral resistance. Antisense oligonucleotides, ribozymes, small interfering RNAs, aptamers and deoxyribozymes constitute classes of oligonucleotide-based compounds designed to target highly conserved or functionally crucial regions contained within the HCV genome. The therapeutic expectation for such compounds is the elimination of HCV from infected individuals. Progress in oligonucleotide-based HCV antivirals towards clinical application depends on development of nucleotide designs that bolster efficacy while minimizing toxicity, improvement in liver-targeting delivery systems, and refinement of small-animal models for preclinical testing.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.319
Teacher spread0.285 · 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 teacher head, 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

Citations9
Published2006
Admission routes1
Has abstractyes

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