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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.

MACHINE LEARNING PREDICTION OF INDOOR PM₂.₅-BOUND DIBENZO[a,h]ANTHRACENE IN CHILDREN’S CHURCH FACILITIES IN SOUTHERN NIGERIA USING MICROCLIMATIC DATA

2026Afrischolar DiscoveryJournalOpen access

10.60787/jcas.vol2no1.1 Full text0 citations

Authors

2 authors across 2 institutions in 1 country.

U. D. ArchibongFirst author
- University of Benin (NG)
as printed: Archibong, Ukeme Donatus
Michael, Christopher UkuegbohoSenior author
- Delta State Polytechnic Ogwashi-Uku (NG)

Fields

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

Toxic Organic Pollutants Impactlevel 3 · 0.52
Air Quality and Health Impactslevel 3 · 0.17
Indoor Air Quality and Microbial Exposurelevel 3 · 0.05

Sources

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

openalexseen September 9, 2026
2026 · Afrischolar Discovery · 0 citations
https://openalex.org/W7133205953

MACHINE LEARNING PREDICTION OF INDOOR PM₂.₅-BOUND DIBENZO[a,h]ANTHRACENE IN CHILDREN’S CHURCH FACILITIES IN SOUTHERN NIGERIA USING MICROCLIMATIC DATA · Sankore