Countries
Institutions
Fields
Rankings
Compare

Search institutions, scholars, countries and publications

Sankore

Named after the University of Sankore in Timbuktu — one of the world’s oldest centres of learning. Every figure here is computed from work-level records in our own graph, never copied from a source’s summary count.

Built from

OpenAlex — works, authorships, subject classification
ROR — institutional identity
ORCID — researcher identity
Crossref — publisher confirmation

Browse

Countries
Institutions
Fields
Rankings
What we cover

Coverage is partial and says so. A country appears with its research output only once its works have been swept; until then the portal shows whatever the graph happens to hold for it and labels it as exactly that.

Application of Machine Learning Algorithms to Predict Rock Types Using Geochemical Data: A Case Study from the Obuasi Gold District, Ghana

2025Earth and environmental sciences libraryBook Chapter

10.1007/978-3-031-97163-1_8 Full text0 citations

Authors

3 authors.

Emmanuel Daanoba SunkariFirst authorCorresponding
Abdullah Bello Muhammed
- University of Mines and Technology (GH)
Abdul BasitSenior author
- University of Mines and Technology (GH)
as printed: Abdul Wahab Basit

Fields

Assignment is probabilistic — a work belongs to several fields in proportions.

Geochemistry and Geologic Mappinglevel 3 · 1.00
Mineral Processing and Grindinglevel 3 · 1.00
Hydrocarbon exploration and reservoir analysislevel 3 · 0.99

Sources

Several sources describing one work is the point — it means the record rests on more than one authority.

openalexseen September 5, 2026
2025 · Earth and environmental sciences library · 0 citations
https://openalex.org/W4412819756

Application of Machine Learning Algorithms to Predict Rock Types Using Geochemical Data: A Case Study from the Obuasi Gold District, Ghana · Sankore