The use of environmental factors as adjuncts to traditional tuberculosis contact investigation.
Bibliographic record
Abstract
SETTING: A 25-year-old university student was diagnosed with cavitary pulmonary and laryngeal tuberculosis following symptoms of underlying cough of 6 months' duration. OBJECTIVES: To estimate the hourly risk of infection (HRI) and examine the role of environmental factors, including room size and ventilation, in modulating this risk. METHODS: Contact investigation. RESULTS: Of 1100 contacts identified, 78.3% (n = 896) received a tuberculin skin test (TST), of whom 27.5% had a positive result. Among 634 Canadian-born contacts tested, 22.7% had a positive TST. The independent risk factors for a positive TST among Canadian-born university students were: > 35 h spent with the index case (adjusted OR 6.6, 95% CI 1.0-44.9) and smaller classroom size (aOR 5.0, 95% CI 1.4-10.0). In the first school term, the HRI among Canadian-born student contacts was 0.9%; in the second term, it was 1.6%. CONCLUSION: There are inherent limitations in generalising findings from an outbreak investigation, due to the considerable variation in the infectiousness of cases. Nevertheless, in situations where the index case has a high degree of infectiousness, and there are numerous contacts with low expected prevalence of infection, the HRI can, together with ventilation measurements, be useful in guiding the extent of contact investigation needed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".