Diversity of Mycobacterium tuberculosis Isolates in an Immigrant Population: Evidence against a Founder Effect
Bibliographic record
Abstract
Population-based studies have used DNA typing of Mycobacterium tuberculosis organisms to estimate the extent of ongoing tuberculosis transmission in various communities and to characterize associated risk factors. The finding of matched DNA "fingerprints" among isolates from an immigrant subgroup may reflect transmission in the adopted country but could also reflect limited diversity among M. tuberculosis organisms within that immigrant community. The authors sought to determine which hypothesis is more likely to explain the high frequency of matched isolates among Haitian-born tuberculosis patients in Montreal, Quebec, Canada. The authors determined the number of different bacterial genotypes in this community as compared with other foreign-born tuberculosis patients and applied a recently described measure of genetic similarity between M. tuberculosis organisms ("genetic distance"). Among 76 Haitian-born tuberculosis patients diagnosed during 1996-1998, the authors identified 47 distinct genotypes on the basis of standard IS6110 DNA typing and categorical analysis. In genetic distance analysis, these 47 genotypes showed as great a genetic diversity as that observed among the 191 distinct genotypes identified in 216 other foreign-born tuberculosis patients. A mycobacterial "founder effect" is unlikely to account for the high proportion of shared isolates among Haitian-born Montrealers. Recent transmission remains the most likely explanation.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".