Reassessment of Sequence-Based Targets for Identification of<i>Bacillus</i>Species
Bibliographic record
Abstract
The Bacillus genus is a large heterogeneous group in need of an efficient method for species differentiation. To determine the current validity of a sequence-based method for identification and provide contemporary data, PCR and sequencing of a 500-bp product encompassing the V1 to V3 regions of the 16S rRNA gene were undertaken using 65 of the 83 type strains of this genus. This region proved discriminatory between most species (70.0 to 100% similarity), the exceptions being clinically relevant B. cereus and B. anthracis as well as nonpathogenic B. psychrotolerans and B. psychrodurans. Consequently, 27 type and clinical strains from the B. cereus group were used to test alternate targets (rpoB, vrrA, and the 16S-23S spacer region) for identification. The rpoB gene proved the best alternate target, with a conserved 4-nucleotide difference between B. cereus and B. anthracis. The high 16S rRNA gene sequence similarities between some strains demonstrated the need for a polyphasic approach to the systematics of this genus. This approach is one focus of the Ribosomal Differentiation of Medical Microorganisms mandate. Accordingly, the 16S rRNA gene sequences generated in this study have been submitted for inclusion into its publicly accessible, quality-controlled database at http://www.ridom_rdna.de/.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".