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Asbestos

2011· other· en· W4244423598 on OpenAlexaboutno aff
Robert L. Virta

Bibliographic record

VenueKirk-Othmer Encyclopedia of Chemical Technology · 2011
Typeother
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsnot available
Fundersnot available
KeywordsAsbestosTremoliteActinoliteChrysotileAsbestos cementPulp and paper industryWaste managementMetallurgyEngineeringMaterials scienceChlorite

Abstract

fetched live from OpenAlex

Abstract The term asbestos is a generic designation referring usually to six types of naturally occurring mineral fibers that are or have been commercially exploited. These fibers belong to two mineral groups: serpentines and amphiboles. The serpentine group is represented by a single asbestiform variety‐chrysotile. There also are five commercial asbestiform varieties of amphiboles‐anthophyllite asbestos, cummingtonite‐grunerite asbestos (amosite), riebeckite asbestos (crocidolite), tremolite asbestos, and actinolite asbestos. Amosite and crocidolite are no longer mined. Nearly all of the asbestos mined after the mid‐1990s was chrysotile. Only very small amounts of actinolite, anthophyllite, and tremolite asbestos may be mined in a few countries. Asbestos was mined in Argentina, Brazil, Canada, China, India, Kazakhstan, and Russia in 2010; world production was estimated to be 1.97 × 10 6 tons. Properties that made asbestos valuable for industrial applications were their thermal, electrical, and sound insulation properties; inflammability; matrix reinforcement (cement, plastic, and resins); adsorption capacity (filtration, liquid sterilization); wear and friction properties (friction materials such as brakes and clutches); and chemical inertia (except in acids). These properties led to the use of asbestos in about 3,000 products by the 1960s. Since about 1995, asbestos‐cement products, including pipe and sheets, accounted for more than 95% of global asbestos consumption as other uses of asbestos have declined. Global consumption of asbestos was estimated to have been about 1.98 × 10 6 tons in 2009. The leading consuming countries in 2009 were Brazil, China, India, Russia, and Thailand, each with more than 100,000 tons of consumption.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.147
Threshold uncertainty score1.000

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.007
GPT teacher head0.235
Teacher spread0.228 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2011
Admission routes1
Has abstractyes

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