Cooking Oils, Salad Oils, and Dressings
Bibliographic record
Abstract
Abstract Lipids used in food products have been conventionally divided into two classes based on their consistency at about 25 °C (72 °F): (i) liquid oils and (ii) solid and semisolid fats. Edible oils can be further divided by their general usage in food, as cooking oil or as salad oil. These types of oils can be characterized by a wide variety of measures that assess attributes such as quality, stability, and nutritional value. Cooking oils are in considerable demand for use in applications such as deep‐fat frying of many food products or in other uses where exposure to higher temperature is desired. However, salad oils are not generally used in applications where the oil is exposed to heat; rather this oil type finds application in foods that are shelf‐stable or refrigerated. One large food use of salad oils is for dressings. Oil‐based dressings are divided into two broad categories by their texture: spoonable dressings (salad dressings, mayonnaise) and pourable dressings.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.046 | 0.011 |
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".