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Record W4241303806 · doi:10.1108/oxan-db258973

Decarbonisation demand will support copper prices

2021· other· en· W4241303806 on OpenAlexaboutno aff

Bibliographic record

VenueEmerald expert briefings · 2021
Typeother
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsLiberian dollarEconomic shortageUs dollarQuarter (Canadian coin)ChinaDemocracyAgricultural economicsSupply and demandNatural resource economicsBusinessCommerceEconomicsGeographyPolitical scienceFinanceExchange ratePoliticsArchaeologyLaw

Abstract

fetched live from OpenAlex

Significance Record imports by China caused demand to exceed supply, creating a market deficit of 1.2% (278,000 tonnes) in 2020. Dollar weakness in the second half of 2020 added to nominal gains, and seasonal fourth-quarter demand provided additional support. Impacts The Democratic Republic of the Congo has postponed its plan to ban copper concentrate exports until the end of April. Barrick is rumoured to be thinking of buying Arizona-based Freeport; this would create a copper-gold mining powerhouse in North America. Ivanhoe’s study of its Kakula mine (Democratic Republic of the Congo) claims it is the world’s most environmentally friendly copper miner.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.075
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0750.013

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 head0.013
GPT teacher head0.258
Teacher spread0.244 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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
Published2021
Admission routes1
Has abstractyes

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