Single-Nucleotide Repeat Analysis for Subtyping <i>Bacillus anthracis</i> Isolates
Bibliographic record
Abstract
Single-nucleotide repeats (SNRs) are variable-number tandem repeats that display very high mutation rates. In an outbreak situation, the use of a marker system that exploits regions with very high mutation rates, such as SNRs, allows the differentiation of isolates with extremely low levels of genetic diversity. This report describes the identification and analysis of SNR loci of Bacillus anthracis. SNR loci were selected in silico, and the loci with the highest diversity were used to design and test locus-specific primers against a number of B. anthracis strains with the same multilocus variable-number tandem repeat analysis (MLVA) genotype. SNR markers that allowed strains with the same MLVA genotype to be differentiated from each other were identified. The resulting SNR marker system can be used as a molecular epidemiological tool in a natural outbreak or bioterrorism event, offering the best chance of distinguishing very closely related isolates.
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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 | 0.000 | 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) | 0.001 | 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".