Bibliographic record
Abstract
Approved GM oilseed crops being grown worldwide include soyabeans, canola and cotton, which are major sources of oil and protein for human and animal feeding. Soyabeans are the most important of these crops since the beans and extracted oil are used as human food. Only the oil from canola and cottonseed are used as human food, the fat-extracted meals being used as animal feed. A striking feature is the high proportion of GM cultivars of these crops being grown, in some countries approaching 100%. Several GM cultivars of these crops have been approved as food/feed sources by regulatory authorities, based on evidence of safety and nutritional composition. Several countries have also approved their cultivation domestically, but this has not been the case in Europe. Results of scientific investigations confirm the approval granted to GM cultivars by regulatory authorities, and contrary findings published by some investigators have not been accepted as credible by the scientific community. Claims of higher contents of pesticide residues in GM oilseed crops are not supported by the scientific evidence. Based on the available scientific evidence it is clear that the approved cultivars of GM oilseeds produce food and feed that is as safe and nutritious as non-GM cultivars.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.051 | 0.034 |
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".