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Marine RNA Virus Quasispecies Are Distributed throughout the Oceans

2019· article· en· W2928153265 on OpenAlexafffund
Marli Vlok, Andrew S. Lang, Curtis A. Suttle

Bibliographic record

VenuemSphere · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsMemorial University of NewfoundlandUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsBiologyRNAViral quasispeciesRNA virusViral evolutionGenomeNonsynonymous substitutionVirusBiological dispersalMarine bacteriophageGeneticsEvolutionary biologyGenePopulation

Abstract

fetched live from OpenAlex

Very little is known about aquatic RNA virus populations and genome evolution. This is the first study that analyzes marine environmental RNA viral assemblages in an evolutionary and broad geographical context. This study contributes the largest marine RNA virus metagenomic data set to date, substantially increasing the sequencing space for RNA viruses and also providing a baseline for comparisons of marine RNA virus diversity. The new viruses discovered in this study are representative of the most abundant family of marine RNA viruses, theMarnaviridae, and expand our view of the diversity of this important group. Overall, our data and analyses provide a foundation for interpreting marine RNA virus diversity and evolution.

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)0.001
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.008
GPT teacher head0.234
Teacher spread0.226 · 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

Citations52
Published2019
Admission routes2
Has abstractyes

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