Molecular Tools for Typing and Branding the Tubercle Bacillus
Bibliographic record
Abstract
During the past two decades, a number of variable genetic sequences have been uncovered that permit molecular typing of Mycobacterium tuberculosis complex (MTC) organisms. Since the determination of the M. tuberculosis, and later M. bovis, genome sequences, the nature of these variable genetic sequences has become more evident, permitting a clearer recognition of which molecular tools lend themselves best to certain applications. In this review, 'classical' genotyping methods for molecular epidemiologic uses are briefly discussed, followed by a more detailed description of post-genomic typing methods, including large sequence polymorphisms otherwise referred to as genomic deletions. Because genomic deletions represent unique event polymorphisms not prone to reversion, these mutations effectively 'brand' bacterial lineages, including species/sub-species of the MTC and specific clades of M. tuberculosis sensu stricto. Genomic deletions therefore provide a new opportunity to accurately classify organisms for diagnostic and epidemiologic purposes, serving as the basis for further study of the natural variability across MTC organisms.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.006 |
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".