Surveillance of Australian workplace Based Respiratory Events (SABRE) in New South Wales
Bibliographic record
Abstract
BACKGROUND: The Surveillance of Australian workplace Based Respiratory Events (SABRE) New South Wales (NSW) scheme is a voluntary notification scheme established to determine the incidence of occupational lung diseases in NSW Australia. AIMS: Data presented in this paper summarize the last 7 years of reporting to SABRE (June 2001 to December 2008). METHODS: Every 2 months, participating occupational physicians, respiratory physicians and general practitioners (accredited by the NSW WorkCover Authority) reported new cases of occupational lung disease seen in their practices. Data collected include gender, age, causal agent and the occupations and industries believed responsible. Estimated incidence was calculated for each disease. RESULTS: Three thousand six hundred and fifty-four cases were notified to the scheme, consisting of 3856 diagnoses. Most of the cases were males (76%). Pleural plaques [1218 (28%)] were the most frequently reported condition, followed by mesothelioma [919 (24%)]. Silicosis [90 (2%)] and occupational asthma [OA; 89 (2%)] were the most frequently reported non-asbestos-related diseases. Estimated rates for mesothelioma, diffuse pleural thickening (DPT) and OA were 83, 83 and 5 cases per million employed males per year, respectively. Trades such as carpenters and electricians associated with the building industry, electricity supply and asbestos product manufacture were the most common occupations and industries reported. CONCLUSIONS: Asbestos-related diseases are the most frequently reported conditions to SABRE NSW. The very low incidence of OA for NSW most likely reflects under-diagnosis as well as under-reporting. Occupational lung disease is still occurring in NSW despite current preventative strategies. The SABRE scheme currently provides the only available information in this area.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".