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Record W2929460817

Alcoa forecasts 2019 alumina surplus on China production rises

2019· article· en· W2929460817 on OpenAlexaboutno aff
Industrial Minerals

Bibliographic record

VenueIndustrial Minerals · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeochemistry and Elemental Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsRefinerySanctionsTonneChinaProduction (economics)Agricultural economicsCapital (architecture)Quarter (Canadian coin)EconomicsBusinessEconomyCommerceEnvironmental scienceEngineeringGeographyEnvironmental engineeringWaste managementMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

The removal of US sanctions on producer Rusal has added strength to Alcoa's forecast of a surplus in alumina in 2019.United States-based Alcoa, the world’s eighth-largest aluminium producer, has forecast that there will be a surplus of alumina in 2019 while it increases aluminium metal shipments. Fastmarkets’ alumina index will be used in a basket of prices to settle contracts on the London Metal Exchange, the exchange announced in January. 2018 supply squeeze In March 2018, Hydro’s Alunorte refinery was forced to reduce its output by 50% in line with state environmental concerns. The current alumina price of less than $400 per tonne reflects this, and we see a potential restart from the second quarter onward, with a return of 3 million tpy putting pressure on marginal Chinese producers,” BMO Capital Markets analyst Kash Kamal 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 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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.026
GPT teacher head0.215
Teacher spread0.189 · 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; both teacher heads agree on what is shown here.

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
Published2019
Admission routes1
Has abstractyes

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