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Parvoviruses of Aquatic Animals

2024· preprint· en· W4399590688 on OpenAlexaffabout
Frederick S.B. Kibenge, Molly Kibenge, Marcos Godoy

Bibliographic record

VenuePreprints.org · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsBiologyShrimpDNA virusParvoviridaeParvovirusVirusFisheryVirologyGenomeGenetics

Abstract

fetched live from OpenAlex

Family Parvoviridae consists of small, non-enveloped viruses with linear, single-stranded DNA genomes of approximately 4-6 kilobases, subdivided into 3 subfamilies: Parvovirinae, Densovirinae and Hamaparvovirinae. Parvoviruses of aquatic animals infect crustaceans, mollusks, and finfish. In this review, these parvoviruses, which are highly host-specific and are associated with mass morbidity and mortality in both farmed and wild aquatic animals are described. They include Cherax quadricarinatus densovirus (CqDV) in freshwater crayfish; Sea star-associated densovirus (SSaDV) in sunflower sea star on the Northeastern Pacific Coast; Clinch densovirus 1 in freshwater mussels in the Clinch River, Virginia, and Tennessee, USA, in subfamily Densovirinae; Hepatopancreatic parvovirus (HPV) and Infectious hypodermal and hematopoietic necrosis virus (IHHNV) in farmed shrimp worldwide; Syngnathid ichthamaparvovirus 1 in gulf pipefish in the Gulf of Mexico and parts of South America; and Tilapia parvovirus (TiPV) in farmed tilapia in China and Thailand, in the subfamily Hamaparvovirinae. In addition, virus megataxonomy has enabled the inclusion of novel parvoviruses detected in both diseased and healthy animals using metagenomic sequencing for virus discovery, such as the novel zander parvovirus from zander in Hungary, novel salmon parvovirus from sockeye salmon smolts in British Columbia-Canada, and Spawner-isolated mortality virus (SMV) from shrimp broodstock in Australia.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.129
GPT teacher head0.401
Teacher spread0.272 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations3
Published2024
Admission routes2
Has abstractyes

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