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Record W4394577701 · doi:10.11647/obp.0373.24

The Copper Supply Gap

2024· book-chapter· en· W4394577701 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOpen Book Publishers · 2024
Typebook-chapter
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCopperEnvironmental scienceMaterials scienceMetallurgy

Abstract

fetched live from OpenAlex

Copper is a critical metal for electrification, and is witnessing a step-change in demand associated with the transition away from fossil fuels to clean energy and electric transportation systems. By 2030, a copper supply gap of ten million metric tons per year is expected, equivalent to the global copper supply required to meet the Paris Agreement targets. This essay discusses the challenges ahead as we seek to close this anticipated supply gap, with a particular focus on the need for new underground mining methods to access deeper copper deposits. The shift to targeting deep underground deposits is pushing the mining industry beyond its experience base, creating a need for novel engineering approaches to mitigate new geological hazards, while also managing new economic risk factors. Success in these endeavours is critical to the advancement of the clean energy transition.

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.

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 categoriesScholarly communication, Insufficient 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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.150
Threshold uncertainty score0.997

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 communication0.0060.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.004

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 head0.025
GPT teacher head0.258
Teacher spread0.233 · 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