Rapeseed and canola oil: production, processing, properties and uses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
1. Rapeseeds and rapeseed oil -- agronomy, production, and trade. Elaine J. Booth, Scottish Agricultural College, Aberdeenshire, UK and Frank D. Gunstone, University of St Andrews and Scottish Crop Research Institute, Dundee, UK. 2. Extraction and refining. Elaine J. Booth, Scottish Agricultural College, Aberdeenshire, UK. 3. Chemical composition of canola and rapeseed oils. W. Nimal Ratnayake, Health Canada, Ottawa, Canada and James K. Daun, Grain Research Laboratory, Winnipeg, Canada. 4. Chemical and physical properties of canola and rapeseed oil. Derick Rousseau, Ryerson University , Toronto, Canada. 5. High erucic oil: its production and uses. Clare Temple--Heald, Croda Chemicals Europe Ltd, Hull, UK. 6. Food uses and nutritional properties. Bruce E. McDonald, Manitoba Health Research Council, Winnipeg, Canada. 7. Non--food uses. Kerr Walker, Scottish Agricultural College, Aberdeenshire, UK. 8. Potential and future prospects for rapeseed oil. Christian Mollers, University of Goettingen, Germany. References. Index
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it