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Record W1807561560 · doi:10.15353/cfs-rcea.v2i2.97

GRAB - GMO 2.0: Genetically modified crops and the push for Africa’s green revolution

2015· article· en· W1807561560 on OpenAlexaffvenue
Matthew A. Schnurr

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsGreen RevolutionAgricultureChinaAgricultural economicsHectareGenetically modified cropsGenetically modified organismAgroforestryGeographyGenetically engineeredAgricultural scienceBiologyEconomics

Abstract

fetched live from OpenAlex

Genetically modified (GM) crops are plants in which the DNA has been engineered using laboratory techniques to express a beneficial trait. Their reception across the globe has been mixed: they form a dominant part of North American agriculture, they have been met with widespread disapproval in Europe, and they are of increasing importance in emerging economies such as India, China and Brazil. Approximately 9 percent of agricultural land worldwide was planted under GM crops in 2014. This figure expanded at a rate of 6 million hectares over the previous year, driven largely by growth in the Global South. Developing countries now account for more than 50 percent of the total acreage planted worldwide, and more than 90 percent of the 18 million farmers cultivating them (James, 2014).

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.115
GPT teacher head0.253
Teacher spread0.139 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2015
Admission routes2
Has abstractyes

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