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Record W2013852459 · doi:10.1371/journal.pone.0069127

The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Does Not Replicate in Syrian Hamsters

2013· article· en· W2013852459 on OpenAlexaff
Emmie de Wit, Joseph Prescott, Laura Baseler, Trenton Bushmaker, Tina Thomas, Matthew G. Lackemeyer, Cynthia Martellaro, Shauna Milne-Price, Elaine Haddock, Bart L. Haagmans, Heinz Feldmann, Vincent J. Munster

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of Manitoba
FundersNational Institutes of HealthNational Institute of Allergy and Infectious DiseasesEuropean Commission
KeywordsMiddle East respiratory syndrome coronavirusSeroconversionVirologyImmunologyBiologyCoronavirusVirusMesocricetusDiseaseMedicineHamsterInfectious disease (medical specialty)Coronavirus disease 2019 (COVID-19)Pathology

Abstract

fetched live from OpenAlex

In 2012 a novel coronavirus, MERS-CoV, associated with severe respiratory disease emerged in the Arabian Peninsula. To date, 55 human cases have been reported, including 31 fatal cases. Several of the cases were likely a result of human-to-human transmission. The emergence of this novel coronavirus prompts the need for a small animal model to study the pathogenesis of this virus and to test the efficacy of potential intervention strategies. In this study we explored the use of Syrian hamsters as a small animal disease model, using intratracheal inoculation and inoculation via aerosol. Clinical signs of disease, virus replication, histological lesions, cytokine upregulation nor seroconversion were observed in any of the inoculated animals, indicating that MERS-CoV does not replicate in Syrian hamsters.

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 categoriesInsufficient 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 score0.049
Threshold uncertainty score0.999

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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.179
GPT teacher head0.319
Teacher spread0.141 · 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

Citations143
Published2013
Admission routes1
Has abstractyes

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