Demographic risk factors of pulmonary colonization by non-tuberculous mycobacteria.
Bibliographic record
Abstract
SETTING: British Columbia (BC), Canada. OBJECTIVE: To determine the risk factors for pulmonary colonization by non-tuberculous mycobacteria (NTM). DESIGN: Retrospective study of subjects colonized by NTM from 1990 to 2006. Subjects without mycobacterial disease and with at least three negative cultures served as controls. RESULTS: Mycobacterium avium complex (MAC) species were the most common NTM. Risk factors of colonization included age > or = 60 years (aOR 2.3), female sex (aOR 1.2), residency in Canada for at least 10 years (aOR 3.8), Canadian-born aboriginal (aOR 1.8), and Canadian-born non-aboriginal (aOR 1.4). Predictors of MAC colonization included White race (aOR 1.6) and residency in Canada for at least 10 years, which was the strongest predictor (aOR 6.7). Aboriginal origin was associated with non-MAC colonization (aOR 1.8), and Canadian-born people from the East/South-East Asian ethnic groups were protected from MAC colonization (aOR 0.2), all aOR P < 0.05. CONCLUSION: Older age, female sex, having been born in Canada, long residency in BC and White race predict pulmonary NTM colonization, while Aboriginal origin predicts non-MAC colonization. Further research is needed to identify environmental NTM sources in BC and to determine their relation to colonization and disease.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".