Foods versus Drugs for Health Promotion: Considerations for Future Directions
Bibliographic record
Abstract
The series of papers in this thematic issue discuss the differences and similarities of foods versus drugs in disease prevention and treatment. The main focus of each contribution is considered in this review. The use as well as advantages and drawbacks of combination therapy employing drugs and foods are also elaborated on. Examples of combining the use of pharmaceuticals and food bioactives including using statins or ezetimibe in conjunction with plant sterols are provided. In summary, the present paper makes a case for adoption of food bioactives in both prevention and treatment approaches to disease, and recommends that functional foods can serve as efficacious adjuncts to pharmacotherapy during all stages of treatment of numerous diseases. Keywords: Bioactives, drugs, food, functional foods, health promotion, mechanisms of action, genes, health, nutrigenomics, targets
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 | 0.018 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.008 | 0.017 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.015 | 0.014 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".