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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.

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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.

Enhancing Lithology Classification From Well Logs Using Weighted Class Training and Bayesian Optimization in Voting Classifiers

2025Journal of Petroleum and Mining EngineeringJournalOpen access

10.21608/jpme.2025.344501.1221 Full text0 citations

Authors

3 authors across 2 institutions in 1 country.

Franklin Chidera ObikaFirst author
- Federal University of Technology Owerri (NG)
Chukwudi Unegbu
- Lagos State Health Service Commission (NG)
Ndubuisi Uchechukwu OkerekeSenior author
- Federal University of Technology Owerri (NG)
as printed: Ndubuisi Okereke

Fields

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

Mineral Processing and Grindinglevel 3 · 0.88
Image Processing and 3D Reconstructionlevel 3 · 0.88
Hydraulic Fracturing and Reservoir Analysislevel 3 · 0.84

Sources

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

openalexseen September 9, 2026
2025 · Journal of Petroleum and Mining Engineering · 0 citations
https://openalex.org/W4411248334

Enhancing Lithology Classification From Well Logs Using Weighted Class Training and Bayesian Optimization in Voting Classifiers · Sankore