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Record W3016501031 · doi:10.1371/journal.pone.0231864

Identification of a novel archaea virus, detected in hydrocarbon polluted Hungarian and Canadian samples

2020· article· en· W3016501031 on OpenAlexaboutno aff
János Molnár, B. Magyar, György Schneider, Krisztián Laczi, Sarshad Koderi Valappil, Árpád L. Kovács, Ildikó K. Nagy, Gábor Rákhely, Tamás Kovács

Bibliographic record

VenuePLoS ONE · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsnot available
FundersMagyarország Kormánya
KeywordsMetagenomicsArchaeaBiologyMethanosarcinaEnvironmental pollutionGenomeVirusBacteriaVirologyGeneticsEnvironmental scienceGeneEnvironmental protection

Abstract

fetched live from OpenAlex

Metagenomics is a helpful tool for the analysis of unculturable organisms and viruses. Viruses that target bacteria and archaea play important roles in the microbial diversity of various ecosystems. Here we show that Methanosarcina virus MV (MetMV), the second Methanosarcina sp. virus with a completely determined genome, is characteristic of hydrocarbon pollution in environmental (soil and water) samples. It was highly abundant in Hungarian hydrocarbon polluted samples and its genome was also present in the NCBI SRA database containing reads from hydrocarbon polluted samples collected in Canada, indicating the stability of its niche and the marker feature of this virus. MetMV, as the only currently identified marker virus for pollution in environmental samples, could contribute to the understanding of the complicated network of prokaryotes and their viruses driving the decomposition of environmental pollutants.

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 score0.537
Threshold uncertainty score0.921

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.037
GPT teacher head0.208
Teacher spread0.172 · 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

Citations14
Published2020
Admission routes1
Has abstractyes

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