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Record W2109571740 · doi:10.1002/ajim.22180

Short, fine and WHO asbestos fibers in the lungs of quebec workers with an asbestos‐related disease

2013· article· en· W2109571740 on OpenAlexaffabout
Georges Adib, France Labrèche, Louise De Guire, Chantal Dion, André Dufresne

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsUniversité de MontréalInstitut de recherche Robert-Sauvé en santé et en sécurité du travailInstitut National de Santé Publique du Québec
Fundersnot available
KeywordsChrysotileAsbestosMedicineAsbestosisMesotheliomaTremoliteAsbestos fibersEnvironmental healthLung cancerFiberLung diseaseLungPathologyInternal medicineComposite material

Abstract

fetched live from OpenAlex

BACKGROUND: The possible role of short asbestos fibers in the development of asbestos-related diseases and availability of lung fiber burden data prompted this study on the relationships between fiber characteristics and asbestos-related diseases among compensated workers. METHODS: Data collected between 1988 and 2007 for compensation purposes were used; lung asbestos fibers content of 123 Quebec workers are described according to socio-demographic characteristics, job histories and diseases (asbestosis, mesothelioma, lung cancer). RESULTS: Most workers (85%) presented chrysotile fibers in their lungs, and respectively 76%, 64%, and 43% had tremolite, amosite, and crocidolite. Half of the total fibers were short, 30% were thin fibers and 20% corresponded to the World Health Organization definition of fibers (length ≥ 5 μm, diameter ≥ 0.2 and <3 μm). Chrysotile fibers were still observed in the lungs of workers 30 years or more after last exposure. CONCLUSION: Our findings stress the relevance of considering several dimensional criteria to characterize health risks associated with asbestos inhalation.

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)0.000
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 score0.105
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.254
Teacher spread0.239 · 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

Citations29
Published2013
Admission routes2
Has abstractyes

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