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Record W6929005006 · doi:10.48380/pfk1-q847

LCT Pegmatite exploration and mining in Africa - an analysis

2024· article· en· W6929005006 on OpenAlexaboutno aff

Bibliographic record

Venuedggv-e-publications · 2024
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsnot available
Fundersnot available
KeywordsPegmatiteChinaGeopoliticsEuropean commissionResource (disambiguation)CommissionProduct (mathematics)AllianceLanguage change

Abstract

fetched live from OpenAlex

LCT pegmatites are the main solid rock resource for battery lithium with a market share of over 50%. The focus of current and future exploration and mining beyond the current main supplier Australia is emerging in southern Africa and Canada. Europe will only be able to cover a good quarter of its own requirements if the currently explored deposits are all mined. Non-European LCT pegmatites are therefore becoming increasingly important. The EC is therefore striving for raw materials partnerships ie with Namibia. But Europe is not alone here. China in particular has become active in several African countries, both entrepreneurially and politically. Investments by private Chinese companies have exceeded the financial resources provided by the EC for the development of raw materials partnerships many times over. Furthermore, European companies play a subordinate role, own mining operators are missing, as are take-offs or backward integration of European OEMs More than this, Chinese companies are increasingly getting involved in or taking over exploration projects. However, the rush for lithium in Africa risks fueling corruption and failing citizens. The presentation provides an overview of the deposits and geopolitical ambitions of the main consumer states as well as the supplier countries in the region under review and ventures a forecast for securing Europe's raw materials in global competition.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.068
GPT teacher head0.326
Teacher spread0.258 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2024
Admission routes1
Has abstractyes

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