Bibliographic record
Abstract
The largest share in the actual production and consumption of vegetable oils falls on sunflower oil and is about 86%. Meanwhile, among agricultural crops there are those that can be used for the production of vegetable oils for food and cosmetic purposes. Since 1992, a movement has begun in the world to restore hemp production, but in the Russian Federation, despite government subsidies, hemp production does not expand due to the lack of specialized equipment and diffi cult licensing. Hemp oil from the seeds of hemp (Cannabis sativa Linnaeus) is included in the country's regulations and can be circulated in the market. The oil belongs to linoleic/linolenic oils and, depending on the region of cultivation, diff ers signifi cantly in fatty acid composition. Hemp oils are characterized by the presence of 46–70% linoleic acid (C18:2, two double bonds) and 26–28% linolenic acid (C18:3). The amount of monounsaturated oleic acid is 6–16%. The amount of saturated fatty acid is 16%. In the USA, Canada, Italy, and the Czech Republic, the modern Finola variety is cultivated, the fatty acid composition of the oil of which is almost 90% represented by unsaturated fatty acids.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".