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An overview of nickel mineralisation in Africa with emphasis on the Mesoproterozoic East African Nickel Belt (EANB)

2016· article· en· W2460880896 on OpenAlexaff
David M. Evans, Jason Hunt, J. R. Simmonds

Bibliographic record

VenueEpisodes · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsBruyère
Fundersnot available
KeywordsNickelGeologyGeochemistryMaterials scienceMetallurgy

Abstract

fetched live from OpenAlex

Nickel production in Africa takes place principally in Botswana, South Africa and Zimbabwe, with much of the South African and Zimbabwean production being a by-product of platinum-group element mining in the Bushveld Complex and Great Dyke. Several large nickel deposits have been discovered elsewhere in Africa but until recently, their development has been hindered by political risk and limitations in energy and transport infrastructure. Most of the continent is significantly underexplored with respect to base metals, including the area covered by the East African Nickel Belt (EANB). The known nickel deposits of the EANB all occur in mafic-ultramafic intrusive rocks of the Mesoproterozoicage Kibaran igneous event. These intrusive bodies take the form of medium to large layered intrusions, small dynamic magma conduits (chonoliths and sills) and dyke swarms. Laterite deposits are developed over exposed dunite and peridotite lithologies in the basal sequence of larger layered intrusions, whereas nickel sulphide deposits are developed at the base of the small chonoliths. Geochronological and geochemical data suggests that all intrusions in the EANB formed in a single magmatic event (1350 to 1400 Ma) and were derived from a picritic parental magma, which was variably contaminated in mid to upper-crustal staging chambers by metasedimentary rocks. As a result, nickel sulphide mineralisation was formed in all of the intrusions, but in most, the grades and tenors are too low to be considered economic in the foreseeable future. In the 1970s, government-led regional surveys identified a large nickel laterite deposit at Musongati in Burundi and a nickel sulphide deposit at Kabanga in the northwest of Tanzania. These deposits have subsequently been explored and delineated by mining companies, but they remain undeveloped due to their distance to the coast and a lack of transport and energy infrastructure. The Kabanga sulphide deposit now comprises a total mineral resource of 58 million tonnes grading 2.6% nickel. The Musongati laterite deposit comprises an overall resource of 122 million tonnes with a grade of 1.4% nickel.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.006
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.058
GPT teacher head0.238
Teacher spread0.180 · 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
GenreReview

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

Citations15
Published2016
Admission routes1
Has abstractyes

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