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Record W1919377205 · doi:10.3389/fmicb.2015.01119

Amdoparvoviruses in small mammals: expanding our understanding of parvovirus diversity, distribution, and pathology

2015· review· en· W1919377205 on OpenAlexafffund
Marta Canuti, Hugh Whitney, Andrew S. Lang

Bibliographic record

VenueFrontiers in Microbiology · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyMinkEvolutionary biologyParvoviridaeHuman viromeZoologyParvovirusGenusVirusEcologyVirologyGenomeGenetics

Abstract

fetched live from OpenAlex

Many new viruses have been discovered recently, thanks in part to the advent of next-generation sequencing technologies. Among the Parvoviridae, three novel members of the genus Amdoparvovirus have been described in the last 4 years, expanding this genus that had contained a single species since its discovery, Aleutian mink disease virus. The increasing number of molecular and epidemiological studies on these viruses around the world also highlights the growing interest in this genus. Some aspects of amdoparvoviruses have been well characterized, however, many other aspects still need to be elucidated and the most recent reviews on this topic are outdated. We provide here an up-to-date overview of what is known and what still needs to be investigated about these scientifically and clinically relevant animal viruses.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.092
GPT teacher head0.341
Teacher spread0.249 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations65
Published2015
Admission routes2
Has abstractyes

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