Occurrence, types, properties and interactions of phenolic compounds with other food constituents in oil-bearing plants
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
Phenolic phytochemicals have become of interest due to their therapeutic potential, particularly with regards to their anti-cancer, anti-inflammatory, hypolipidemic, and hypoglycemic properties. An evolving area of research involving phenolics in foods and their products pertains to the functional, biological, and nutritional consequences resulting from the binding between certain phenolic compounds and the macronutrient and micronutrient constituents of foods. The goal of this review is to provide a summary of studies investigating endogenous phenolic interactions with major components in food systems, including carbohydrates, proteins, lipids, minerals and vitamins, with a focus on the phenolic compounds and nutrients in oil-bearing plants. Another major objective is to provide a comprehensive overview of the chemical nature of phenolic interactions with food constituents that could affect the quality, nutritional and functional properties of foods. Such information can assist in the discovery and optimization of specific phenolic complexes in plant-based foods that could be utilized towards various applications in the food, nutraceutical and pharmaceutical industries.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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