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Pulmonary mineral fibers after occupational and environmental exposure to asbestos in the Russian chrysotile industry

2000· article· en· W2019621223 on OpenAlexaboutno aff
Antti Tossavainen, E. Kovalevsky, Esa Vanhala, Timo Tuomi

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2000
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsnot available
Fundersnot available
KeywordsChrysotileTremoliteAsbestosAmphiboleMedicineOccupational exposureTalcActinoliteToxicologyEnvironmental healthMetallurgyMaterials scienceBiology

Abstract

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BACKGROUND: As an indicator of occupational, domestic, and environmental exposure, the level and type of asbestos fibers were determined from lung tissue samples of workers and residents who resided in the area of the world's largest asbestos mine at Asbest, Russia. METHODS: Electron microscopy was used to analyze and measure the concentration of asbestos fibers in a series of 47 autopsies at the Asbest Town Hospital. Work histories were obtained from pathology reports and employment records. RESULTS: In 24 chrysotile miners, millers, and product manufacturers, the pulmonary concentrations of retained fibers (over 1 microm in length) were 0. 8-50.6 million f/g for chrysotile, and < 0.1-1.9 million f/g for amphiboles (tremolite and anthophyllite). The concentrations were lower in 23 persons without any known occupational contact with asbestos; 0.1-14.6 million f/g for chrysotile, and < 0.1-0.7 million f/g for amphiboles. On average, 90% of all inorganic fibers were chrysotile, and 5% tremolite/anthophyllite. No amosite or crocidolite fibers were detected in any of the samples. CONCLUSIONS: The mean and range of pulmonary chrysotile concentrations were about the same as reported previously from the Canadian mining and milling industry. In the Russian samples, the mean concentration of tremolite fibers were less by at least one order of magnitude. Occupational contact was the most important source of asbestos exposure.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.252
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.

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
Published2000
Admission routes1
Has abstractyes

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