The Changing Landscape of Malnutrition: Why It Matters
Bibliographic record
Abstract
Nutrition is an integral part of the prevention and management of the most prevalent conditions faced by today's primary care providers. This book is aimed at physicians around the world who treat patients from all walks of life. The first section is devoted to the basic principles of nutrition, covering the fundamentals of body composition, energy balance, and appetite, as well as the importance of the different macro- and micronutrients. The following section builds on the principles of the first by focusing on the special needs for specific circumstances, including pregnancy, exercise, food allergies and religion. The third part provides an overview of our latest understanding of various disease states and how they are influenced by nutrition. The final part on Food Policy takes a bird's eye view, offering perspectives on global sustainability, the rapidly changing face of malnutrition and the role played by the food industry in consumer health. This book is a practical reference source that will guide physicians on how to use nutrition as a tool to prevent and cure disease.
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.013 | 0.021 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.009 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".