Population Analysis of Streptococcus suis Isolates from Slaughtered Swine by Use of Minimum Core Genome Sequence Typing
Bibliographic record
Abstract
Streptococcus suis, an important zoonotic pathogen, is a highly diverse species with only a subset of strains that cause disease in humans. Our previous study proposed a minimum core genome (MCG) sequence typing method and defined seven MCG groups, with MCG group 1 as the prevalent group causing human infections. In this study, we identified a set of 10 single nucleotide polymorphisms (SNPs) distributed in six genes that were used to identify the seven MCG groups. The 10 SNPs were typed for 179 S. suis isolates collected from slaughtered pigs. The most prevalent groups among the tested isolates were MCG groups 6 and 7. Most of the isolates (147/179) were genotyped as mrp negative, epf negative, sly negative, and CDS2157 positive. The 179 isolates were also typed by multilocus sequence typing (MLST) and divided into 115 sequence types (STs), 111 of which were new. The 6 serotypes (29, 11, 5, 12, 30, and 2) represented 72.3% of the serotyped isolates. Our data show that the typing assay facilitates the application of genome data to the surveillance of S. suis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".