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Record W2138572375 · doi:10.1128/jcm.44.3.777-782.2006

Single-Nucleotide Repeat Analysis for Subtyping <i>Bacillus anthracis</i> Isolates

2006· article· en· W2138572375 on OpenAlexaff
Chad W. Stratilo, Christopher T. Lewis, Louis Bryden, Michael R. Mulvey, Doug Bader

Bibliographic record

VenueJournal of Clinical Microbiology · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsUniversity of SaskatchewanPublic Health Agency of CanadaDefence Research and Development Canada
Fundersnot available
KeywordsMultiple Loci VNTR AnalysisBacillus anthracisSubtypingBiologyVariable number tandem repeatGeneticsGenotypeLocus (genetics)MicrosatelliteGenetic diversityTandem repeatIn silicoComputational biologyGenomeGenePopulationBacteriaMedicine

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.748
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.336
Teacher spread0.300 · 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 teacher head, 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

Citations48
Published2006
Admission routes1
Has abstractyes

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