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Record W2116933090 · doi:10.1093/annhyg/46.suppl_1.125

Airborne Asbestos Fibres in Steam Tunnels: A Qualitative Analysis by PLM and a Quantitative Analysis by PCOM and TEM/EDS

2002· article· en· W2116933090 on OpenAlexaffabout
A. Dufresne, Marcus Anthes, Brenda Lohanny Passos Santos, Claire Infante‐Rivard

Bibliographic record

VenueThe Annals of Occupational Hygiene · 2002
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsMcGill University
Fundersnot available
KeywordsAsbestosOccupational hygieneOccupational exposureAsbestos fibersThreshold limit valuePhase contrast microscopyEnvironmental scienceMaterials scienceMineralogyMetallurgyChemistryOpticsEnvironmental healthMedicineOccupational safety and healthPhysics

Abstract

fetched live from OpenAlex

A question often asked of industrial hygienists is whether or not asbestos fibres can be propagated by air draughts on altered insulating material. An occupational hygiene survey was conducted during the summer of 1999 throughout the steam tunnels of a university campus to determine airborne concentrations of asbestos fibres in order to answer this question. Results were compared with the so-called clearance test standard (0.01 f/ml used in the Province of Québec) for work liable to produce asbestos dust emission. Some 3.2% of the results were over the clearance test standard when airborne concentrations of asbestos fibres were determined by phase contrast optical microscopy. However, 41.9% of the results were over the clearance test standard when ambient samples were counted by transmission electron microscopy/energy dispersive spectroscopy (TEM/EDS) for asbestos fibres only and reached 48.4% for all TEM mineral fibres. Of the TEM/EDS results, 3.2% were >0.1 f/ml, the threshold limit value proposed by ACGIH.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
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 head0.095
GPT teacher head0.394
Teacher spread0.299 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2002
Admission routes2
Has abstractyes

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