Mesothelioma: Scientific clues for prevention, diagnosis, and therapy
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
Mesothelioma affects mostly older individuals who have been occupationally exposed to asbestos. The global mesothelioma incidence and mortality rates are unknown, because data are not available from developing countries that continue to use large amounts of asbestos. The incidence rate of mesothelioma has decreased in Australia, the United States, and Western Europe, where the use of asbestos was banned or strictly regulated in the 1970s and 1980s, demonstrating the value of these preventive measures. However, in these same countries, the overall number of deaths from mesothelioma has not decreased as the size of the population and the percentage of old people have increased. Moreover, hotspots of mesothelioma may occur when carcinogenic fibers that are present in the environment are disturbed as rural areas are being developed. Novel immunohistochemical and molecular markers have improved the accuracy of diagnosis; however, about 14% (high-resource countries) to 50% (developing countries) of mesothelioma diagnoses are incorrect, resulting in inadequate treatment and complicating epidemiological studies. The discovery that germline BRCA1-asssociated protein 1 (BAP1) mutations cause mesothelioma and other cancers (BAP1 cancer syndrome) elucidated some of the key pathogenic mechanisms, and treatments targeting these molecular mechanisms and/or modulating the immune response are being tested. The role of surgery in pleural mesothelioma is controversial as it is difficult to predict who will benefit from aggressive management, even when local therapies are added to existing or novel systemic treatments. Treatment outcomes are improving, however, for peritoneal mesothelioma. Multidisciplinary international collaboration will be necessary to improve prevention, early detection, and treatment.
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 | 0.001 |
| 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) | 0.000 | 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