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Record W4310525890 · doi:10.1128/msystems.00582-22

RNA Viruses Linked to Eukaryotic Hosts in Thawed Permafrost

2022· article· en· W4310525890 on OpenAlexaff
Ruonan Wu, Eric Bottos, Vincent Danna, James Stegen, Janet Jansson, Michelle Davison

Bibliographic record

VenuemSystems · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant and Fungal Interactions Research
Canadian institutionsThompson Rivers University
FundersPacific Northwest National LaboratoryBiological and Environmental Research
KeywordsBiologyPermafrostRNAVirologyComputational biologyGeneticsEcologyGene

Abstract

fetched live from OpenAlex

Permafrost is thawing at a rapid pace in the Arctic with largely unknown consequences on ecological processes that are fundamental to Arctic ecosystems. This is the first study to determine the composition of RNA viruses in thawed permafrost. Other recent studies have characterized DNA viruses in thawing permafrost, but the majority of DNA viruses are bacteriophages that target bacterial hosts. By contrast RNA viruses primarily target eukaryotic hosts and thus represent potential pathogenic threats to humans, animals, and plants. Here, we find that RNA viruses in permafrost are novel and distinct from those in other habitats studied to date. The COVID-19 pandemic has heightened awareness of the importance of potential environmental reservoirs of emerging RNA viral pathogens. We demonstrate that some potential pathogens were detected after an experimental thawing regime. These results are important for understanding critical viral-host interactions and provide a better understanding of the ecological roles that RNA viruses play as permafrost thaws.

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 score0.003
Threshold uncertainty score0.005

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 studies0.0010.000
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 head0.029
GPT teacher head0.305
Teacher spread0.276 · 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

Citations33
Published2022
Admission routes1
Has abstractyes

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