The Ontario Universal Typing of Tuberculosis (OUT‐TB) Surveillance Program – What It Means to You
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) is a serious disease that is transmitted primarily by the airborne route. Effective disease control and outbreak management requires the timely diagnosis, isolation and treatment of infected individuals with active disease; contact tracing to identify secondary cases likely to benefit from treatment of latent infection; and laboratory identification or confirmation of epidemiologically linked cases. TB genotyping enables the comparison of Mycobacterium tuberculosis complex (MTBC) strains and the identification of cases that may or may not be linked. The increased availability of molecular methods for genotyping has allowed for greater discrimination of MTBC strains and greatly enhanced understanding of TB transmission patterns. OBJECTIVE: To improve TB surveillance and control in Ontario, the Public Health Laboratories of the Ontario Agency for Health Protection and Promotion has introduced the Ontario Universal Typing of Tuberculosis (OUT-TB) Surveillance Program. METHODS: The first isolate from every new TB case will be genotyped with two rapid molecular methods: spoligotyping and mycobacterial interspersed repetitive unit-variable-number tandem repeat typing. MTBC isolates with nonunique genotypes and, thus, potentially linked to other TB cases, will also be genotyped by IS6110 restriction fragment length polymorphism analysis. CONCLUSION: By providing TB control programs using these new genotyping tools, and using traditional and new case investigation methods (eg, social network analysis), this new program will provide a clearer picture of TB in Ontario, and permit more effective use of public health resources and improve disease control.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.009 | 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".