Bibliographic record
Abstract
Part 1 Approaching Drug-Nutrient Interactions 1 An Introduction to Drug-Nutrient Interactions Joseph I. Boullata 2 Drug Disposition and Response Robert B. Raffa 3 Drug Transporters Richard H. Ho and Richard B. Kim 4 Drug-Metabolizing Enzymes Thomas K. H. Chang 5 Nutrient Disposition Francis E. Rosato, Jr. Part 2 Influence of Nutrition Status on Drug Disposition and Effect 6 Influence of Protein-Calorie Malnutrition on Medication Charlene W. Compher and Joseph I. Boullata 7 Influence of Overweight and Obesity on Medication Joseph I. Boullata Part 3 Influence of Food, Nutrients, or Supplementation on Drug Disposition and Effect 8 Drug Absorption with Food David Fleisher, Burgunda V. Sweet, Ameeta Parekh, and Joseph I. Boullata 9 Specific Dietary Components and Medication Karl E. Anderson 10 Grapefruit and Other Fruit Juices Interactions with Medicines David G. Bailey 11 Positive Drug-Nutrient Interactions Imad F. Btaiche, Burgunda V. Sweet, and Michael D. Kraft 12 Interaction of Natural Products with Medication and Nutrients Lingtak-Neander Chan 13 Drug-Nutrient Interactions in Patients Receiving Enteral Nutrition Carol J. Rollins 14 Drug-Nutrient Interactions in Patients Receiving Parenteral Nutrition Jay M. Mirtallo Part 4 Influence of Medication on Nutrition Status, Nutrient Disposition & Effect 15 Drug-Induced Changes to Nutritional Status Jane M. Gervasio 16 Influence of Cardiovascular Medication on Nutritional Status Nima M. Patel and Anna M. Wodlinger Jackson 17 Influence of Neurological Medication on Nutritional Status Marianne S. Aloupis and Ame L. Golaszewski 18 Drug-Nutrient Interactions Involving Folate Patricia Worthington and Leslie Schechter 19 Drug-Nutrient Interactions that Impact on Mineral Status Sue A. Shapses, Yvette R. Schlussel, and Mariana Cifuentes Part 5 Drug-Nutrient Interactions by Life Stage 20 Drug-Nutrient Interactions in Infancy and Childhood Laureen Murphy Kotzer, Maria R. Mascarenhas, and Elizabeth Wallace 21 Drug-Nutrient Interaction Considerations in Pregnancy and Lactation Myla E. Moretti and Danela L. Caprara 22 Drug-Nutrient Interactions in the Elderly Bruce P. Kinosian and Tanya C. Knight-Klimas Part 6 Drug -Nutrient Interactions in Specific Conditions 23 Drug-Nutrient Interactions and Immune Function Adrianne Bendich and Ronit Zilberboim 24 Drug-Nutrient Interactions in Patients with Chronic Cancer Todd W. Canada 25 Drug-Nutrient Interactions in Transplantation Matthew J.Weiss, Vincent T. Armenti, Nicole Sifontis, Jeanette M. Hasse 26 Drug-Nutrient Interactions in Patients with Chronic Infections Steven P. Gelone and Judith A. O'Donnell
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.115 | 0.086 |
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".