Application of Mycobacterial Interspersed Repetitive Unit Typing to Manitoba Tuberculosis Cases: Can Restriction Fragment Length Polymorphism Be Forgotten?
Bibliographic record
Abstract
Since 1993, all Mycobacterium tuberculosis isolates recovered in the province of Manitoba, Canada, have been genotyped by the standard IS6110-restriction fragment length polymorphism (RFLP) method for routine surveillance, prevention, and control purposes. To date, our laboratory has collected 1,290 isolates, from which we have identified approximately 390 unique fingerprint patterns or "types." Although the standard method is well known for being a lengthy and labor-intensive procedure, a more efficient alternative for typing tuberculosis isolates, the mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) method, has recently gained acceptance. Consequently, all isolates acquired in 2003 (n = 126) were typed by both methods in order to determine the utility of replacing the RFLP method with MIRU typing for all future isolates. Application of Hunter's discriminatory index to the available study population showed that the MIRU method was close in discriminatory power (D) to the RFLP method (D(MIRU) = 0.831 to 0.984 versus D(RFLP) = 0.821 to 0.997). Clustering of isolates by using MIRU data correlated with RFLP-derived clustering, lending useful information for either an investigation or confirmation of an incidence of recent transmission. In addition, it was determined that each predominant RFLP type in Manitoba had a corresponding, recognizable MIRU type. It is conceivable that in the future RFLP typing can be replaced with MIRU for real-time, ongoing tuberculosis surveillance in the province.
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How this classification was reachedexpand
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 | 0.002 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".