MétaCan
Menu
Back to cohort

Phylogenetic Analysis of Classical Swine Fever Virus Isolates from Peru

2010· article· en· W1581828009 on OpenAlexaff
Mariluz Araínga, Tamiko Hisanaga, Kevin Hills, K. Handel, John Pasick

Bibliographic record

VenueTransboundary and Emerging Diseases · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsCladePhylogenetic treeOutbreakMonophylyBiologyVirologyPhylogeneticsVirusGeneticsGene

Abstract

fetched live from OpenAlex

Classical swine fever (CSF) is considered to be endemic in Peru with outbreaks reported to the World Organization for Animal Health as recently as 2008 and 2009. Nevertheless, little is known regarding the genetic subgroup(s) of CSF virus that are circulating in Peru or their relationship to recent CSF viruses that have been isolated from neighbouring South American countries or other parts of the world. In this study, we molecularly characterize CSF viruses that were isolated from domestic pigs from different regions of Peru from the middle of 2007 to early 2008. All virus isolates were found to belong to genetic subgroup 1.1, consistent with the subgroup of viruses that have been identified from other South American countries. Although the Peruvian isolates are most closely related to viruses from Colombia and Brazil, they form a monophyletic clade, which suggests they have a distinct evolutionary history.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.013
GPT teacher head0.233
Teacher spread0.220 · 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 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

Citations9
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueTransboundary and Emerging DiseasesSame topicAnimal Disease Management and EpidemiologyFrench-language works237,207