Population-based asbestosis surveillance in British Columbia
Bibliographic record
Abstract
OBJECTIVES: To investigate the use of multiple health data sources for population-based asbestosis surveillance in British Columbia, Canada. METHODS: Provincial health insurance registration records, workers' compensation records, hospitalisation records, and outpatient medical service records were linked using individual-specific study identifiers. The study population was restricted to individuals > or = 15 years of age living in the province during 1992-2004. RESULTS: 1170 new asbestosis cases were identified from 1992 to 2004 for an overall incidence rate of 2.82 (men: 5.48, women: 0.23) per 100,000 population; 96% of cases were male and average (SD) age was 69 (10) years. Although the annual number of new cases increased by 30% during the surveillance period (beta = 2.36, p = 0.019), the observed increase in annual incidence rates was not significant (beta = 0.02, p = 0.398). Workers' compensation, hospitalisation and outpatient databases identified 23%, 48% and 50% of the total new cases, respectively. Of the new cases, 82% were identified through single data sources, 10% were only recorded in the workers' compensation records, and 36% only in each of the hospitalisation and outpatient records. 84% of hospitalisation cases and 83% of outpatient cases were not included in the workers' compensation records. The three data sources showed different temporal trends in the annual number of new cases and annual incidence rates. CONCLUSIONS: Single data sources were not sufficient to identify all new cases, thus leading to serious underestimations of the true burden of asbestosis. Integrating multiple health data sources could provide a more complete picture in population-based surveillance of asbestosis and other occupational diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".