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Record W2106498300 · doi:10.1186/s12985-014-0197-9

Characterization of a new genotype of avian bornavirus from wild ducks

2014· article· en· W2106498300 on OpenAlexaboutno aff
Jianhua Guo, H. L. Shivaprasad, Raquel R. Rech, Jill Heatley, Ian R. Tizard, Susan Payne

Bibliographic record

VenueVirology Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyVirologyGenotypeGeneticsGene

Abstract

fetched live from OpenAlex

BACKGROUND: Avian bornaviruses (ABV) are a recently described group of intranuclear negative-stranded RNA viruses (Order Mononegavirales, Family Bornaviridae). At least 13 different ABV genotypes have been described. One genotype, the Canada goose genotype (ABV-CG), has been isolated from geese and swans and is widely distributed across North America. RESULTS: We have isolated and characterized a previously undescribed genotype of avian bornavirus from the brains of wild ducks. This new genotype, provisionally designated ABV genotype MALL, was detected in 12 of 83 mallards, and 1 of 8 wood ducks collected at a single location in central Oklahoma. The virus was cultured on primary duck embryo fibroblasts, fragments were cloned, and its genome sequence of 8904 nucleotides determined. This new genotype has 72% nucleotide identity and 83% amino acid identity with the ABV-CG genotype previously shown to be present in geese and swans. Histologic and immunohistochemical examination of the brains and eyes of four positive ducks indicated the presence of virus-infected neurons and glia in their cerebrums and retinas in the absence of inflammation. CONCLUSIONS: More than one genotype of ABV is circulating in North American waterfowl. While the infected ducks were not observed to be suffering from overt disease, based on the immunohistochemistry, we speculate that they may have suffered some visual impairment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.769
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.015
GPT teacher head0.262
Teacher spread0.248 · 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.

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

Citations27
Published2014
Admission routes1
Has abstractyes

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