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Global spread and evolution of viral haemorrhagic septicaemia virus

2011· article· en· W1855998727 on OpenAlexaboutno aff
Jonathon Studer, Daniel Janies

Bibliographic record

VenueJournal of Fish Diseases · 2011
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsnot available
FundersIowa State UniversityOhio State University
KeywordsBiologyPhylogenetic treeVirusVirologyPhylogeneticsNucleoproteinRhabdoviridaeFisheryZoologyGeneGeneticsRabies virus

Abstract

fetched live from OpenAlex

Viral haemorrhagic septicaemia virus (VHSV) is a rhabdovirus that infects over 48 species of teleosts and is lethal in many. VHSV threatens marine and aquatic fisheries. VHSV was first discovered outside Europe in 1988 in fish from the Pacific coast of North America. In 1994, VHSV was discovered in Newfoundland. In 2003, VHSV was isolated from fish in Lake St. Clair (Michigan and Ontario). In this study, we used 46 nucleotide sequences for the glycoprotein gene from 12 studies and 150 nucleotide sequences for the nucleoprotein gene from nine studies. We combined phylogenetics and a geographic information system to visualize the transmission paths of VHSV lineages. We also reconstructed the spread of VHSV lineages through optimization of geographic data for viral isolates on phylogenetic trees. We demonstrate that VHSV was transmitted from the North Atlantic Ocean and/or Baltic Sea to the Atlantic coast of North America and Japan in independent events. From the Atlantic coast, the virus was transmitted independently to the Laurentian Great Lakes and the Pacific coast of Canada and the contiguous United States. From the Pacific Northwest, the virus was transmitted to Asia and Alaska in independent events. These results clarify the debate ongoing in the literature on the geographic spread of VHSV.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
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 head0.010
GPT teacher head0.222
Teacher spread0.212 · 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

Citations17
Published2011
Admission routes1
Has abstractyes

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