MétaCan
Menu
Back to cohort
Record W1589999019

Resuscitating the Rare Earths

2011· article· en· W1589999019 on OpenAlexaboutno aff
Peter Gwynne

Bibliographic record

VenueResearch-Technology Management · 2011
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsRare earthGovernment (linguistics)ChinaBusinessProduction (economics)Natural resource economicsPolitical scienceLawEarth scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

Rare earths are the oddballs of the chemical world--17 elements, many with almost unpronounceable names, that occupy their own special space in the periodic table and possess unusual magnetic, catalytic, and luminescent properties. In recent years, the rare earths have gained another distinction: The industrialized world needs rapidly increasing quantities of them. That's because trace amounts of rare earths play vital roles in the production of high-technology products ranging from smartphones to specialized glasses to wind turbines and electric cars. Geopolitical stresses are increasing attention to, and worry about, rare earths. Since about 2002, China has dominated their production. According to consultant James Hedrick, 97 percent of the world's supply of rare earths--and about 93 percent of the rare earth elements used in the United States--are mined in China. The Chinese government has not been reluctant to emphasize its control over these vital elements; last July, it announced that it would cut its export quotas by more than 70 percent. Early this year, the government announced that it had placed all mining of rare earths in one of its provinces under its national planning authority. Even before those announcements, Western companies had started efforts to open new mines or reopen sources of supply that had closed. And, encouraged in part by the U.S. Department of Energy (DOE), efforts are under way to recycle rare earths and to develop means of using them more efficiently. The race to create non-Chinese sources is critical because demand for the elements is increasing while geologists have identified few new deposits. From electronics to energy technologies Small quantities of rare earths are in almost every one of our electronic devices, says Donald Ranta, CEO of Canadian company Rare Earth Resources, Ltd. iPhones, iPads, cell phones, computer hard drives, and television sets and screens all require rare earths to make them work. In addition, you cannot produce a hybrid or electric automobile without using rare earths. the majority of the little motors in autos that drive seats and windows up and down and provide power steering are made from neodymium But neodymium provides just one of the rare earth components of those magnets. They also include praseodymium in small amounts, Ranta continues. And some of these magnets also contain 3 to 10 percent of dysprosium, which allows the magnets to reach higher temperatures and still maintain their strength. Rare earth elements also provide valuable assists to energy technologies, including solar and wind power, electric vehicles, and low-energy lights. We have identified five different rare earths that are critical for clean energy and are at supply risk, says Diana Bauer, a policy analyst at DOE who is team leader of the department's critical materials strategy group. Neodymium, dysprosium, terbium, europium, and yttrium are valuable for end use in wind turbines, photovoltaics, and energy-efficient electric vehicles and fluorescent lighting. lanthanum and praseodymium are used in batteries. So critical are rare earths to the production of clean energy products that Mark Smith, CEO of Colorado-based mining firm Molycorp Minerals, calls them green elements. Although China dominates the supply, underground courses of rare earth ores exist around the world. Countries with potentially ruinable amounts include Australia, Austria, Canada, France, Russia, South Africa, and the United States. Since digging up and processing individual elements is extremely expensive, it's fortunate that the rare earths tend to exist in clusters. They tend to live together, but not in consistent relative proportions, Bauer explains. In other words, some rare earths are rarer than others. Exponential growth With potential applications for them continually expanding, the worldwide demand for rare earths of all types has grown exponentially. …

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)0.006
metaresearch head score (Gemma)0.036
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: Empirical · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.036
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.006
Scholarly communication0.0080.011
Open science0.0030.011
Research integrity0.0150.024
Insufficient payload (model declined to judge)0.0460.026

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 head0.117
GPT teacher head0.330
Teacher spread0.213 · 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
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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueResearch-Technology ManagementSame topicExtraction and Separation ProcessesFrench-language works237,207