Evaluation of Charcoal Usage and Its Influence on Deforestation in Makurdi Metropolis Benue State, Nigeria
Bibliographic record
Abstract
Charcoal is the dark grey residue consisting of impure carbon obtained from vegetation substance and produced by pyrolysis, the heating of wood in the absence of oxygen. Charcoal is considered the major source of energy for the inhabitants of Makurdi metropolis. The study was conducted to assess the consumption of charcoal in Makurdi metropolis. Five council wards were selected purposively for data collection. The selected wards are noted for having large quantities of charcoal and consumers almost all year round. The wards selected are Agan, Fiidi, Wadata, Modern Market, and North Bank. From each council ward, 20 respondents were drawn using a random sampling technique. 100 respondents were selected and interviewed using a pre-tested checklist (questionnaire) to collect primary data. From the result, Prosopis africana was the highest used tree species for charcoal with 83.5% then Vitellaria paradoxa with 7.9%. Also, 88% of the respondents preferred charcoal for cooking in providing food for the family because of its affordability compared to other cooking energy sources. Therefore, it is inferred that charcoal has a positive impact on the lives of consumers since affordability is considered the main reason why the majority of households use charcoal. However, the continuous use of forest trees threatens the future of our forest estate and biodiversity leading to land degradation, endangering of species and enhancement of global warming. Therefore, Alternative energy sources should be encouraged for household fuel to ease the pressure on charcoal.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".