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.

Machine learning methods for modeling conventional and hydrothermal gasification of waste biomass: A review

2022Bioresource Technology ReportsJournal

10.1016/j.biteb.2022.100976 Full text113 citations

Authors

4 authors across 5 institutions in 4 countries.

Great C. UmenwekeFirst author
Inioluwa Christianah Afolabi
- Ladoke Akintola University of Technology (NG)
Emmanuel I. Epelle
Jude. A. OkolieSenior authorCorresponding
as printed: Jude A. Okolie

Fields

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

Subcritical and Supercritical Water Processeslevel 3 · 1.00
Thermochemical Biomass Conversion Processeslevel 3 · 1.00
Catalysts for Methane Reforminglevel 3 · 1.00

Sources

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

openalexseen September 9, 2026
2022 · Bioresource Technology Reports · 113 citations
https://openalex.org/W4210462253

Machine learning methods for modeling conventional and hydrothermal gasification of waste biomass: A review · Sankore