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Record W2901683766

Higher Q1 NEV sales bode well for battery raw material demand

2018· article· en· W2901683766 on OpenAlexaboutno aff
Carrie Shi

Bibliographic record

VenueIndustrial Minerals · 2018
Typearticle
Languageen
FieldEngineering
TopicElectric Vehicles and Infrastructure
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)ChinaElectrificationBusinessElectric vehicleAgricultural economicsAgricultural scienceEngineeringCommerceElectricityEconomicsEnvironmental scienceGeographyElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

Output and sales of electric vehicles both up by more than 150% year-on-year, creating good prospects for the lithium, graphite and cobalt markets. China’s output of new electric vehicles (NEVs) rose year-on-year in the first quarter of 2018, underpinned by the country’s continued push toward electrification - a stance that many believe will support the prices for lithium, graphite and cobalt. China’s total production of 149,998 NEVs, including both pure electric vehicles (PEVs) and plug-in hybrids, in the first quarter of this year was up by 156.9% from the corresponding quarter in 2017, according to data released by the China Association of Automobile Manufacturers (CAAM). Sales of NEVs rose to 142,577 units in January-March, up by 154.3% from the first three months of 2017, it added.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
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)0.0010.000

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 head0.024
GPT teacher head0.231
Teacher spread0.207 · 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
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
Published2018
Admission routes1
Has abstractyes

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