MétaCan
Menu
Back to cohort
Record W4212956662 · doi:10.1128/mbio.03718-21

Inhibition of Protein <i>N-</i> Glycosylation Blocks SARS-CoV-2 Infection

2022· article· en· W4212956662 on OpenAlexaff
Aitor Casas-Sánchez, Alessandra Romero-Ramirez, Eleanor Hargreaves, Cameron C. Ellis, Brian Grajeda, Igor L. Estevao, Edward I. Patterson, Grant L. Hughes, Igor C. Almeida, Tobias Zech, Álvaro Acosta-Serrano

Bibliographic record

VenuemBio · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicvaccines and immunoinformatics approaches
Canadian institutionsBrock University
FundersNational Institute on Minority Health and Health DisparitiesEconomic and Social Research CouncilBiotechnology and Biological Sciences Research CouncilUniversity of Texas at El PasoNational Institutes of HealthUniversity of OxfordNational Institute of Allergy and Infectious DiseasesMedical Research CouncilRoyal SocietyNational Institute for Health and Care ResearchNational Institute for Health Research Health Protection Research UnitPublic Health EnglandLiverpool School of Tropical MedicineEngineering and Physical Sciences Research CouncilUK Research and InnovationWellcome Trust
KeywordsVirologyGlycosylationSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Coronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakBiologySars virusMicrobiologyComputational biologyMedicineInfectious disease (medical specialty)DiseaseOutbreakGenetics

Abstract

fetched live from OpenAlex

, including that of several variants. As new SARS-CoV-2 variants, with various degrees of resistance against current vaccines, are likely to continue appearing, halting virus glycosylation using repurposed human drugs could result in a complementary strategy to reducing the spread of COVID-19 worldwide.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.229
Teacher spread0.215 · 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 designBench or experimental
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

Citations45
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuemBioSame topicvaccines and immunoinformatics approachesFrench-language works237,207