Bibliographic record
Abstract
The plant breeding technology commonly known as genetic modification has offered significant benefits to farmers in terms of economy as well as production. Canola ( Brassica napus ) is an oilseed crop and, worldwide, the majority of the canola grown is genetically engineered as it is tolerant to destructive insects and herbicides. The oil from canola is extracted by pressing and used as food and feed for farm animals to enhance production of milk and meat. Canola is rich in both monounsaturated fatty acids (MUFA) and polyunsaturated fats of canola oil, the latter rich in ω-6 and ω-3 fatty acids. Most research studies indicate GM canola to be safe for consumption although a few are concerned about its impact on the environment, human health, and food safety. The introduction of a herbicide-resistant trait in canola has reduced overall herbicide usage by 15.8 million kg in Canada alone, which has enabled farmers to grow sustainability and has encouraged the development of the biotechnology industry. In fact, because of this aspect and its greater health benefits, GM canola is slowly being accepted and it is considered trendy to consume it.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.009 |
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".