The Diagnosis and Attribution of Asbestos-related Diseases in an Australian Context: Report of the Adelaide Workshop on Asbestos-related Diseases. October 6–7, 2000
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Predictions of future cases of mesothelioma in Australia to the year 2020 are in the order of a total of 10,000 new cases. Compensation claims are testing the attribution in a particular case between occupational asbestos exposure and lung cancer. The cost of the problem necessitates clarifying and standardizing the criteria for a confident diagnosis of asbestos-related disease. The possibility of differences in criteria that determine attribution of asbestos to a disease prompted a consensus meeting of pathologists, epidemiologists, physicians, oncologists, radiologists, and others to define current thinking and to agree on an Australian document based on the scientific evidence for establishing diagnoses and attribution data of asbestos-related diseases in Australia. The participants' findings are reported.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it