Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) has been a notifiable disease since 1924 and remains an important and serious global public health challenge. Understanding the patterns and characteristics of TB are key to controlling and preventing further spread of the disease. OBJECTIVE: To provide an overview of national TB surveillance data collected through two national surveillance systems and to highlight important trends in recent years. METHODS: Trends in the incidence of TB since 1924 are presented. Descriptive results from the Canadian Tuberculosis Reporting System (CTBRS) and the Canadian Tuberculosis Laboratory Surveillance System (CTBLSS) are presented, with a focus on the years from 2002 to 2012. No statistical tests of significance were performed. RESULTS: Since the 1940s, both the number of reported TB cases and the overall Canadian incidence rate have declined. Males have always accounted for the greatest percentage of cases overall and individuals between the ages of 25 and 34 have typically accounted for the largest number of reported cases relative to other age groups. From 2002 to 2012, 66% of reported TB cases were foreign-born, but the highest burden of TB was in the Canadian-born Aboriginal population, with an average incidence rate five times that of the overall Canadian rate. Reported drug resistance in Canada remains consistently below international levels. CONCLUSION: Overall, Canada has one of the lowest TB disease rates in the world. However, foreign-born individuals and Aboriginal people continue to be disproportionately represented among cases diagnosed in Canada. Surveillance systems like the CTBRS and CTBLSS are fundamental in providing information needed to target resources where they can be most effective.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".