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Record W2883245912 · doi:10.15273/ijge.2018.03.015

The Potentials of Scientific and Industrial Collaborations in the Field of REE through China’s Belt and Road Initiative

2018· article· en· W2883245912 on OpenAlex
George Barakos, Helmut Mischo

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.

venuePublished in a venue whose home country is Canada.
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

VenueInternational Journal of Georesources and Environment · 2018
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsChinaContext (archaeology)Work (physics)SkepticismBusinessEuropean unionSupply chainSustainable developmentPolitical scienceInternational tradeEngineeringMarketingGeographyLaw

Abstract

fetched live from OpenAlex

Within the framework of trade deals and infrastructure investments, China also wants to build a "belt of scientific cooperation" with countries and international organisations involved in the Belt and Road Initiative. This could create an opportunity for involvement of several European countries that have so far treated China’s initiative with skepticism about the coherence and practicality of the project. A crucial issue that concerns both China and the European Union in the recent years is the establishment of an undisrupted supply of critical raw materials to satisfy the consumption demands of the modern high-tech world that we live in. Among the listed critical raw materials are the rare earth elements (REE). Accordingly, the development of an extended and sustainable REE supply chain is a significant research field in which both sides could collaborate and benefit from. It is crucial for the involved countries to utilise their advantages, work together and share knowledge to tackle technical, economic and environmental issues that govern the global rare earth industry. Hence, in this paper the possibilities of a potential cooperation are investigated in the context of collaborative research projects, academic networking, workshops and training for young scientists. The aim is to seek, find and bridge any gaps that exist between the two sides with a view to strong academic and industrial collaborations.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.108

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)0.0000.000

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 head0.022
GPT teacher head0.269
Teacher spread0.246 · 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