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Record W2759337883

Quartz Corp: : HPQ demand slowing

2015· article· en· W2759337883 on OpenAlexaboutno aff
James Sean Dickson

Bibliographic record

VenueIndustrial Minerals · 2015
Typearticle
Languageen
FieldEngineering
TopicMining Techniques and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsQuartzRaw materialEngineeringGeologyWaste managementArchaeologyMineralogyMaterials scienceGeographyMetallurgyChemistry
DOInot available

Abstract

fetched live from OpenAlex

The Quartz Corp., which owns a 30,000 tpa high purity quartz (HPQ) facility in Norway and mines in Spruce Pine, US, and Norway, has told IM that the market for HPQ is positive, with demand continuing to grow in the main end use sectors. At the Malvina project located 200km east of Montreal, Quebec Quartz recorded a weighted average of 99.57% silica (SiO[subscript]2 ) for its eight samples, which the company claimed proved the suitability of the resource for HPQ feedstock and silicon metal applications. Earlier in January, Quebec Quartz logged an average of 99.46% quartz at its Montpetit Quarry site, from nine out of 10 drill cores. Silica from the property, which is located 7km south of Saint Clotilde de Chateauguay, a suburb of Montreal, could be used in HPQ sand end uses, in addition to HPQ and silicon metal applications, the company said.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.548
Threshold uncertainty score0.644

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.000
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.5480.328

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 head0.122
GPT teacher head0.248
Teacher spread0.126 · 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.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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