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Record W2127052485 · doi:10.1111/gbi.12052

Silicified virus‐like nanoparticles in an extreme thermal environment: implications for the preservation of viruses in the geological record

2013· article· en· W2127052485 on OpenAlexaff
Xiaotong Peng, Hongyan Xu, Brian Jones, Shi Chen, Huaiyang Zhou

Bibliographic record

VenueGeobiology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of Alberta
FundersNational Key Research and Development Program of ChinaChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsNanoparticleVirusGeothermal gradientHot springHost (biology)Extreme environmentMicrobial matBiofilmChemistryGeologyBiologyMineralogyCyanobacteriaMaterials scienceBacteriaNanotechnologyVirologyEcologyPaleontology

Abstract

fetched live from OpenAlex

Biofilms that grow around Gumingquan hot spring (T = 71 °C, pH = 9.2) in the Rehai geothermal area, Tengchong, China, are formed of various cyanobacteria, Firmicutes, Aquificae, Thermodesulfobacteria, Desulfurococcales, and Thermoproteales. Silicified virus-like nanoparticles, 40-200 nm in diameter, are common inside the microbial cells and the extracellular polymeric substances around the cells. These nanoparticles, which are formed of a core encased by a silica cortex, are morphologically akin to known viruses and directly comparable to silicified virus-like particles that were produced in biofilms cultured in the laboratory. The information obtained from examination of the natural and laboratory-produced samples suggests that viruses can be preserved by silicification, especially while they are still encased in their host cells. These results expand our views of virus-host mineral interaction in extreme thermal environments and imply that viruses can be potentially preserved and identified in the geological record.

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 score0.006

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 studies0.0000.001
Scholarly communication0.0010.000
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 head0.069
GPT teacher head0.275
Teacher spread0.206 · 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

Citations34
Published2013
Admission routes1
Has abstractyes

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