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Record W1916502630 · doi:10.5376/mpb.2011.02.0011

NERICA: A Hope for Fighting Hunger and Poverty in Africa

2011· article· en· W1916502630 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMolecular Plant Breeding · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyBiologyBiotechnologyDevelopment economicsEconomic growthEconomics

Abstract

fetched live from OpenAlex

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”.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.896
Threshold uncertainty score0.127

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.074
GPT teacher head0.218
Teacher spread0.144 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it