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Record W2761717757

Lithium: : Year in Review 2014

2015· article· en· W2761717757 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIndustrial Minerals · 2015
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsLithium hydroxideLithium carbonateGloomLithium (medication)BiddingEngineeringBattery (electricity)BusinessOperations managementMarketingChemistryMedicine
DOInot available

Abstract

fetched live from OpenAlex

2014 followed in the wake of two major mergers in the market - both involving the same company. China's Tianqi Lithium Group formally took over Australia's Talison Lithium in September 2013, following a 10-month process. Rockwood Holdings, which initially lost out on the bidding process, then acquired a 49% interest in Talison in December 2013. It was not all doom and gloom in the market as technology partnerships sprung up, making costs lower and projects more attractive. Lithium Americas, which is developing the Olaroz project, began operating its lithium extraction technology, developed with POSCO and Canada's Energi Group also unveiled its own processing technology, which it said could produce up to 50,000 tpa lithium carbonate. Demand over the next few years is slated to come from the battery industry. Tesla Motors' Gigafactory will need up to 25,000 tpa lithium chemicals - most likely hydroxide - at full capacity. An uptick of 20% of total global demand and 50% up on battery demand.

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 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 score0.466
Threshold uncertainty score0.689

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)0.0000.001

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 head0.111
GPT teacher head0.306
Teacher spread0.195 · 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