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Record W2999394803 · doi:10.3390/pathogens9010050

Genotypic Comparison between Streptococcus suis Isolated from Pigs and Humans in Thailand

2020· article· en· W2999394803 on OpenAlexaff
Anusak Kerdsin, Dan Takeuchi, Aniroot Nuangmek, Yukihiro Akeda, Marcelo Gottschalk, Kazunori Oishi

Bibliographic record

VenuePathogens · 2020
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsUniversité de Montréal
FundersKasetsart University Research and Development InstituteJapan Society for the Promotion of ScienceKasetsart University
KeywordsStreptococcus suisSerotypeCarriageOutbreakVeterinary medicineBiologyGenotypeHygieneMultilocus sequence typingVirologyMedicine

Abstract

fetched live from OpenAlex

Streptococcus suis is a zoonotic pathogen of economic significance to the swine industry. The number of infected cases is increasing in humans worldwide. In this study, we determined the prevalence and diversity of S. suis carriage in slaughterhouse pigs in Phayao province, Thailand, where an outbreak occurred in 2007. The overall S. suis carriage rate was 35.2% among slaughterhouse pigs. The prevalence rates of serotypes 2 and 14 (the major serotypes infected in humans) were 6.7% and 2.6%, respectively. In both serotypes, 70.4% of isolates of serotypes 2 and 14 revealed sequence types and pulsotypes identical to human isolates in Thailand. It is suggested that pathogenic strains of S. suis are a risk factor for occupational exposure to pigs or the consumption of raw pork products. Food safety, hygiene, and health education should be encouraged to reduce the risk group.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 studies0.0000.000
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 head0.047
GPT teacher head0.303
Teacher spread0.256 · 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 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

Citations61
Published2020
Admission routes1
Has abstractyes

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