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Record W2115952550 · doi:10.1099/vir.0.80438-0

An approach for genogrouping of Japanese isolates of aquabirnaviruses in a new genogroup, VII, based on the VP2/NS junction region

2005· article· en· W2115952550 on OpenAlexaboutno aff
Toyohiko Nishizawa, Shinichi Kinoshita, Mamoru Yoshimizu

Bibliographic record

VenueJournal of General Virology · 2005
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyPhylogenetic treeInfectious pancreatic necrosis virusVirologyGenotypeStrain (injury)VirusPhylogeneticsGeneGenetics

Abstract

fetched live from OpenAlex

Aquabirnaviruses, represented by Infectious pancreatic necrosis virus (IPNV), have been isolated from epizootics in salmonids and a variety of aquatic animals in the world; six genogroups of aquabirnaviruses have been identified. In comparisons of nucleotide sequences of the VP2/NS junction region, maximum nucleotide diversities of 30.8 % were observed among 93 worldwide aquabirnavirus isolates. A phylogenetic tree revealed the existence of a new genogroup, VII, for Japanese aquabirnavirus isolates from marine fish and molluscan shellfish. Nucleotide diversities between genogroups VII and I-VI were 18.7 % or greater. At the nucleotide level, Japanese IPNV isolates from epizootics in salmonids were nearly identical to a genogroup I strain from the USA or Canada. It is suggested that Japanese IPNV isolates belonging to genogroup I were originally introduced from North American sources, whereas Japanese aquabirnavirus isolates of genogroup VII were from marine aquatic animals indigenous to Japan.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.023
GPT teacher head0.252
Teacher spread0.229 · 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

Citations107
Published2005
Admission routes1
Has abstractyes

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