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Record W2109023822 · doi:10.1093/annhyg/meq076

Epidemiology of Malignant Mesothelioma—An Outline

2010· article· en· W2109023822 on OpenAlexaboutno aff
J C McDonald

Bibliographic record

VenueThe Annals of Occupational Hygiene · 2010
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsnot available
Fundersnot available
KeywordsTremoliteChrysotileAsbestosActinoliteMesotheliomaAmphiboleEnterobiusEpidemiologyMedicineEnvironmental healthPathologyGeologyMaterials scienceMetallurgyImmunology

Abstract

fetched live from OpenAlex

In the 1960s and 1970s, well designed case-referent studies put beyond doubt that exposure to airborne asbestos fibres was a cause of malignant mesothelioma. Some 35 cohort mortality studies in a large variety of industries during the 20-year period, 1974-1994, showed a wide range of outcomes, but in general that the risk was higher in exposures which included amphiboles rather than chrysotile alone. Real progress began, however, with discoveries along several lines: the link between pleural changes and mineralogy, the concept and importance of biopersistence, the developments in counting and typing mineral fibres in lung tissue, and data on amphibole mining in South Africa and Australia for comparison with that on chrysotile in Canada and Italy. This led to the recognition of the potential contamination in North America of chrysotile with tremolite. A survey in Canada in 1980-1988 and other surveys demonstrated that crocidolite, amosite, and tremolite could explain almost all cases of mesothelioma. Effective confirmation of this was finally achieved with data on vermiculite miners in Libby, Montana, in the years 1983-1999, where exposure was to tremolite-actinolite and/or other amphibole fibres alone.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.135
GPT teacher head0.411
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations47
Published2010
Admission routes1
Has abstractyes

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