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Record W4380853846 · doi:10.1016/j.chom.2023.05.003

The coronavirus recombination pathway

2023· review· en· W4380853846 on OpenAlexaff
Heather Wells, Cassandra M. Bonavita, Isamara Navarrete‐Macias, Blake Vilchez, Angela L. Rasmussen, Simon J. Anthony

Bibliographic record

VenueCell Host & Microbe · 2023
Typereview
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of Saskatchewan
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthNational Science Foundation
KeywordsRecombinationBiologyCoronavirusMechanism (biology)Homologous recombinationRecombinant DNATransmission (telecommunications)GenomeFLP-FRT recombinationComputational biologyCoronavirus disease 2019 (COVID-19)GeneticsEvolutionary biologyGenetic recombinationGeneComputer sciencePhysicsDisease

Abstract

fetched live from OpenAlex

Recombination is thought to be a mechanism that facilitates cross-species transmission in coronaviruses, thus acting as a driver of coronavirus spillover and emergence. Despite its significance, the mechanism of recombination is poorly understood, limiting our potential to estimate the risk of novel recombinant coronaviruses emerging in the future. As a tool for understanding recombination, here, we outline a framework of the recombination pathway for coronaviruses. We review existing literature on coronavirus recombination, including comparisons of naturally observed recombinant genomes as well as in vitro experiments, and place the findings into the recombination pathway framework. We highlight gaps in our understanding of coronavirus recombination illustrated by the framework and outline how further experimental research is critical for disentangling the molecular mechanism of recombination from external environmental pressures. Finally, we describe how an increased understanding of the mechanism of recombination can inform pandemic predictive intelligence, with a retrospective emphasis on SARS-CoV-2.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.007

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 head0.116
GPT teacher head0.403
Teacher spread0.287 · 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.

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

Citations72
Published2023
Admission routes1
Has abstractyes

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