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Prevalence of enzootic simian viruses among urban performance monkeys in Indonesia

2005· article· en· W1613994480 on OpenAlexafffund
Michael A. Schillaci, Lisa Jones‐Engel, Gregory Engel, Yasmina Arditi Paramastri, Entang Iskandar, Brenda K. Wilson, Jonathan S. Allan, Randall C. Kyes, Robin Watanabe, Richard Grant

Bibliographic record

VenueTropical Medicine & International Health · 2005
Typearticle
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersNational Center for Research ResourcesNational Institutes of HealthConnaught FundUniversity of Toronto
KeywordsEnzooticSimianVirologyGeographyBiologyVeterinary medicineMedicineVirus

Abstract

fetched live from OpenAlex

Animal reservoirs are the most important sources of emerging infectious diseases that threaten human populations. Global travel and tourism bring ever-increasing numbers of humans into contact with animals, increasing the likelihood of cross species transmission of infectious agents. Non-human primates come into contact with humans in a variety of contexts and may harbor infectious agents with zoonotic potential. We investigated the prevalence of infection with enzootic simian viruses among 20 urban performance monkeys (Macaca fascicularis) in Jakarta, Indonesia. This report documents for the first time evidence of infection with four simian viruses in urban performance monkeys. Simian foamy virus was detected by PCR in 52.9% of the macaques. Antibodies to simian retrovirus were detected in 10.5% of the macaques. Antibodies to Cercopithecine Herpesvirus 1, were detected in 5.3% of the macaques. Similarly, antibodies to simian T-cell lymphotropic virus were detected in 5.3% of the macaques. No evidence of infection with simian immunodeficiency virus was detected in these macaques. These results suggest that urban performance monkeys are a reservoir for enzootic simian viruses known to be capable of infecting humans.

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 score0.040
Threshold uncertainty score0.632

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 head0.029
GPT teacher head0.345
Teacher spread0.316 · 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

Citations47
Published2005
Admission routes2
Has abstractyes

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