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Record W2612724532 · doi:10.18632/oncotarget.17694

Characterization of Sudan Ebolavirus infection in ferrets

2017· article· en· W2612724532 on OpenAlexafffund
Andrea Kroeker, Shihua He, Marc-Antoine de La Vega, Gary Wong, Carissa Embury‐Hyatt, Xiangguo Qiu

Bibliographic record

VenueOncotarget · 2017
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsCanadian Food Inspection AgencyUniversité LavalUniversity of ManitobaPublic Health Agency of Canada
FundersNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health ResearchChinese Academy of SciencesPublic Health Agency of Canada
KeywordsEbolavirusVirologyVirusOutbreakAnimal modelTransmission (telecommunications)Guinea pigBiologyEbola virusAnimal speciesGold standard (test)MedicineZoologyGenetics

Abstract

fetched live from OpenAlex

Sudan virus (SUDV) outbreaks in Africa are highly lethal; however, the development and testing of novel antivirals and vaccines for this virus has been limited by a lack of suitable animal models. Non-human primates (NHP) remain the gold standard for modeling filovirus disease, but they are not conducive to screening large numbers of experimental compounds and should only be used to test the most promising candidates. Therefore, other smaller animal models are a valuable asset. We have recently developed a guinea-pig adapted SUDV virus that is lethal in guinea pigs. In our current study, we show that ferrets are susceptible to wild-type SUDV, providing a small animal model to directly study clinical isolates, screen experimental anti-SUDV compounds and potentially study viral transmission.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.287

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)0.0000.000

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 head0.042
GPT teacher head0.372
Teacher spread0.330 · 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

Citations32
Published2017
Admission routes2
Has abstractyes

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