Transgenics: Why Their Adoption And Consumption Should Be Approached With Caution In Nigeria
Bibliographic record
Abstract
Genetic Engineering which involves the removal of genetic material from one organism and splicing it into the chromosomes of another is today set to revolutionalize agriculture. It has given rise to a new set of organisms known as Genetically Modified Organism (GMOs or transgenics). The major advantage of GMO crops are yield increases as well as reduction in pesticide and herbicide use. According to a report by an industry group GMO crops are today flourishing across the globe accounting for about US$44 billion in crops in five leading countries including the US, Argentina, China, Canada and Brazil. Worldwide, 53 million hectares were planted with GMO crops in 2002 with the US accounting for 68% of that average. About 15% of all corn, 30% of all cotton and more than 50% of soyabean grown across the world today are genetically engineered. In spite of their high potential however, there is need to exercise caution in the adoption and consumption GMO crops in Nigeria. Their health and environmental implications are yet to be subjected to long term scientific investigations. Fallouts from past scientific discoveries give credence to this call. For instance, nobody new at the time DDT was discovered that DDT sprayed over a broad area would be bio-magnified through the food chain and concentrated hundreds of thousands of times in the human body. As well, when CFCs were created, they were hailed as a great discovery-inert compounds, great carriers for aerosol sprays. Only when millions of tons of CFCs were liberated into air many years later did we discover their scavenging effect on ozone in the upper atmosphere. (P. C. Aju And I. O. Ezeibekwe. Transgenics: Why Their Adoption And Consumption Should Be Approached With Caution In Nigeria. Researcher. 2010;2(12):62-66). (ISSN: 1553-9865). http://www.sciencepub.net.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".