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Record W4380359198 · doi:10.1021/cen-10119-buscon1

Canada competes for battery projects

2023· article· en· W4380359198 on OpenAlexaboutno aff
Matt Blois

Bibliographic record

VenueC&EN Global Enterprise · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsSubsidyGovernment (linguistics)IncentiveBusinessBattery (electricity)ElectricityRenewable energyFinanceInvestment (military)Joint ventureEngineeringEconomicsCommercePolitical sciencePolitics

Abstract

fetched live from OpenAlex

Canada is attracting lithium-ion battery manufacturing projects by increasing subsidies while highlighting its access to renewable electricity and battery raw materials. The success comes despite billions of dollars in incentives from the Inflation Reduction Act (IRA) designed to lure projects to the US. Canada’s latest success came in May when a joint venture between General Motors and the South Korean chemical firm Posco decided to increase its investment in a battery cathode plant already under construction in Quebec . The governments of Canada and Quebec offered $300 million in financing for the plant. Canada is also negotiating with Umicore to determine how much support it will provide for a planned cathode manufacturing facility in Ontario. And the government told Volkswagen in April that it would match the tax credits offered by the US to attract a battery cell plant to Ontario, a deal worth billions of dollars. The Canadian Critical

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)0.002
metaresearch head score (Gemma)0.008
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.108
Threshold uncertainty score0.781

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0210.004
Scholarly communication0.0120.003
Open science0.0020.005
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0450.005

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 head0.016
GPT teacher head0.292
Teacher spread0.276 · 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
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
Published2023
Admission routes1
Has abstractyes

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