New and current approaches for isolation, identification, and genotyping of<i>Mycobacterium bovis</i>
Bibliographic record
Abstract
Modern mycobacteriology laboratories are highly specialized, utilizing equipment designed specifically for mycobacterial isolation, identification, and genotyping. Over the years biochemical testing has been replaced by molecular methods such as nucleic acid probes, lateral flow assays, polymerase chain reaction, and more recently proteomic approaches such as MALDI-TOF mass spectrophotometry. Standardized genotyping methods such as the 43-spacer spoligotyping (spacer oligonucleotide typing) assay and the 24 mycobacterial interspersed repetitive unit-variable number of tandem repeat (MIRU-VNTR) have been adopted throughout the international community, making possible broad genomic comparisons across laboratories and countries. Many comprehensive national genotyping databases have been created, and epidemiologists rely heavily on them for outbreak investigations. When spoligotyping and variable number tandem repeat are insufficient to distinguish isolates, whole genome sequencing is a realistic option, providing invaluable information in the investigation of disease transmission.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.011 |
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".