Multilocus Sequence Typing Scheme That Provides Both Species and Strain Differentiation for the <i>Burkholderia cepacia</i> Complex
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A single multilocus sequence typing (MLST) scheme was developed for precise characterization of the opportunistic pathogens of Burkholderia cepacia complex (BCC), a group composed of at least nine closely related species. Seven conserved housekeeping genes were selected after a comparison of five Burkholderia species, and a collection of strains was subjected to nucleotide sequence analysis using a nested PCR amplification approach for each gene. MLST differentiated all nine current BCC species and identified 114 sequence types within a collection of 119 strains. No differentiation was found between strains recovered from environmental or clinical sources. The improved resolution in strain identification offered by MLST was able to identify previously characterized epidemic strain lineages and also demonstrated the presence of four novel potential species groups within the complex. There was also evidence for recombination having an important role in the recent evolution of individual BCC species. This highly transferable, validated, MLST scheme provides a new means to assist in species identification as well as unambiguous strain discrimination of the BCC by a single approach. It is also the first MLST scheme designed at the outset to incorporate multiple species and should facilitate global epidemiological investigations of the BCC.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it