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Record W4242882305 · doi:10.1108/oxan-db205473

Global copper market hit by China's slowdown

2015· other· en· W4242882305 on OpenAlexaboutno aff

Bibliographic record

VenueEmerald expert briefings · 2015
Typeother
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsSlowdownChinaQuarter (Canadian coin)Consumption (sociology)PaymentRevenueCopperEconomic slowdownHedgeProduction (economics)Tax revenueEconomicsBusinessAgricultural economicsEconomyFinanceGeographyEconomic growthMetallurgy

Abstract

fetched live from OpenAlex

Subject Copper market. Significance Copper prices dropped by 11.7% in January due to aggressive shorting by Chinese hedge funds. In the following four months, the metal staged a recovery, only to lose 19% since mid-May, hitting a six-year low on August 26. Physical activity during the traditionally strong second quarter proved disappointing, with demand hit by China's economic slowdown and its declining copper demand. The production cuts recently announced by Glencore have given some relief to the market. Impacts Molybdenum (a by-product from copper mines) prices fell by 15% in the second quarter, pressuring producers' margins further. Botswana will defer for one year the payment of a royalty tax, aiming at job preservation and miners' support. Vedanta's Zambian smelter's imports of copper feed from Chile will link the two copper centres for the first time.

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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0160.001

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 head0.242
Teacher spread0.235 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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