Tuberculosis in Norway by country of birth, 1986-1999.
Bibliographic record
Abstract
OBJECTIVE: To estimate the standardised incidence ratio (SIR) of TB among the foreign-born in Norway. METHOD: The expected number of TB cases was calculated by applying the sex- and age-specific incidence rates for those born in Norway to the corresponding foreign-born population. The SIR was measured as the ratio between observed and expected number of cases. RESULTS: The expected number of TB cases was between zero and three for all selected countries; the observed number of cases was significantly higher. The SIR was highest for Africa (160, 95%CI 144-175) and lowest for USA/Canada (0.4, 95%CI 0.1-1.0). It was 883 for Somalia (95%CI 775-991), 122 for Vietnam (95%CI 106-139), 119 for Pakistan (95%CI 105-134), 115 for the Philippines (95%CI 91-144) and 49 for former Yugoslavia (95%CI 40-57). The SIR for all the foreign-born was 21 (95%CI 20-22), giving a population attributable risk of 38%. It was highest in the age group 15-39 years (95, 95%CI 89-101), and lowest for those 65 years and older (3, 95%CI 2.1-3.3). The SIR for extrapulmonary TB was also high in those aged 15-39 years (159, 95%CI 146-173). CONCLUSION: SIRs for TB differ by country and continent of birth. Understanding local epidemiology and immigration patterns will help better target prevention efforts.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".