NERICA: A Hope for Fighting Hunger and Poverty in Africa
Bibliographic record
Abstract
NERICA (new rice for Africa), a new promising African upland rice species, is getting into the limelight in West-Africa, it has been developed through crossing African rice species (known for resistant to disease and drought) and Asian rice species (for its high yield potential) with the assistance from Japan, UNDP and other organizations. Its varieties are being hailed as a “miracle crop” that can bring Africa its long-promised green revolution in rice that is why a powerful coalition of governments, research institutes, private seed companies and donors are leading a major effort to spread NERICA seeds to all the continent’s rice fields. At first, the NERICA researchers insisted that they did not intend NERICA to replace local diversity. Indeed, the incorporation of new seeds is nothing new for African farmers because as usual, new varieties are often mixed with old ones and become part of the selection process, contributing to the local genetic heritage, and now it is perfectly adapted to the harsh growing environment and low-input conditions of upland rice ecologies in sub-Saharan Africa (SSA), where smallholder farmers lack the means to irrigate and apply chemical fertilizers or pesticides and it responds even better to higher inputs. This promising new rice for Africa combine high yield, short duration, resistance to pest and diseases, more protein and amino-acid content, iron and zinc, and an acceptable taste, and since its creation so far, the New Rice for Africa (NERICA) has carved a special niche for itself among upland rice farmers in sub-Saharan Africa (SSA): today, it is a symbol of hope for food security in the SSA and as the Africa rice center declares with pride on its web pages, the New Rice for Africa, a technology from Africa for Africa, has become a symbol of hope for food security in a region of the world where one-third of the people are undernourished and half the population struggle to survive on US $1 a day or less; also the Africa rice center director-general Papa Abdoulaye Seck comments, “NERICA is a powerful weapon on Africa’s fight against hunger and poverty”.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".