Quantifying Alternative Food Potential of Agricultural Residue in Rural Communities of Sub-Saharan Africa
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
African countries have been severely affected by food insecurity such that 54% of the population (73 million people) are acutely food insecure, in crisis or worse. Recent work has found technical potential for feeding humanity during global catastrophes using leaves as stop-gap alternative foods. To determine the potential for adopting agricultural residue (especially crop leaves) as food in food-insecure areas, this study provides a new methodology to quantify the calories available from agricultural residue as alternative foods at the community scale. A case study is performed on thirteen communities in Nigeria to compare national level values to those available in rural communities. Two residue utilization cases were considered, including a pessimistic and an optimistic case for human-edible calories gained. Here, we show that between 3.0 and 13.8 million Gcal are available in Nigeria per year from harvesting agricultural residue as alternative food. This is enough to feed between 3.9 and 18.1 million people per year, covering from 10 to 48% of Nigeria’s current estimated total food deficit.
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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 | 0.000 | 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 | 0.001 |
| 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 it