Development of Multiple-Locus Variable-Number Tandem-Repeat Analysis for <i>Yersinia enterocolitica</i> subsp. <i>palearctica</i> and Its Application to Bioserogroup 4/O3 Subtyping
Bibliographic record
Abstract
Yersinia enterocolitica bioserogroup 4/O3 is the predominant causative agent of yersiniosis in Europe and North America. Multiple-locus variable-number tandem-repeat analysis (MLVA) was developed to improve the resolution power of classical genotyping methods. MLVA based on six loci was able to distinguish 76 genotypes among 91 Y. enterocolitica isolates of worldwide origin and 41 genotypes among 51 nonepidemiologically linked bioserogroup 4/O3 isolates, proving that it has a high resolution power. However, only a slight correlation of the MLVA genotypes and the geographic distribution of the isolates was observed. Although MLVA was also capable of distinguishing strains of Y. enterocolitica subsp. palearctica O9 and O5,27, there was only a minor correlation between the MLVA genotypes and serogroups. MLVA may be a helpful tool for epidemiological investigations of Y. enterocolitica subsp. palearctica outbreaks.
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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 | 0.000 |
| 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) | 0.001 | 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".