MétaCan
Menu
Back to cohort
Record W4405411303

An industrial mineral for the next millenium

2001· article· en· W4405411303 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2001
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsMineralMining engineeringEngineeringMetallurgyMaterials science
DOInot available

Abstract

fetched live from OpenAlex

Talc is a mineral of high quality and from chemical point of view it is Mg3Si04010 /OH/2. It usually contains different additional minerals that signigicantly affect its color and most of all its quality. The quality is decreased by the existence of Fe3+, pyrite and oxide Mn. Talc is used mainly in the paper manufacturing, cosmetic industry, glass industry, as a chemical catalyzator, ingredient in making explosives, in pharmaceutics and car industry.Some of the biggest producers of talc are: China - 2.35 mills tons/year, the USA - 1.0 mills tons/year, India - 500.00 kt/year, Finland - 425 kt/year, and Brazil with 325 kt/year. The most important deposits are located in: Finland (Sotkano deposit), in the USA (deposits in the state of New York, Virginia and Vermont) in Canada (province of Ontariou), Australia (Three Springs deposit) etc.Among one of the first companies being interested in this deposit of talc (along with the Rima Muran Ltd) were companies from Germany Gebruder Dorfner and Thyssen Schachtbau. The result of the detailed research of the deposit performed in 1994 was a Feasibility Study. This deposit with 28 milions tons of talc belongs to the group of most important deposits in the world.Initial acivities began in September 2000 and they are still in progress.The first ton will be placed into themarket during this year. The deposit lies about 350 meters beneath the earth surface. The whole body of talc is 2700 meters from West-East and 820 meters from North-South. The average depth of the deposit is 200 meters.

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 categoriesScholarly communication, 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.431
GPT teacher head0.553
Teacher spread0.123 · 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
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

Citations0
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicExtraction and Separation ProcessesFrench-language works237,207