Nutrition, ecology and nutritional ecology: toward an integrated framework
Bibliographic record
Abstract
Summary 1. The science of nutritional ecology spans a wide range of fields, including ecology, nutrition, behaviour, morphology, physiology, life history and evolutionary biology. But does nutritional ecology have a unique theoretical framework and research program and thus qualify as a field of research in its own right? 2. We suggest that the distinctive feature of nutritional ecology is its integrative nature, and that the field would benefit from more attention to formalizing a theoretical and quantitative framework for developing this. 3. Such a framework, we propose, should satisfy three minimal requirements: it should be nutritionally explicit, organismally explicit, and ecologically explicit. 4. We evaluate against these criteria four existing frameworks (Optimal Foraging Theory, Classical Insect Nutritional Ecology, the Geometric Framework for nutrition, and Ecological Stoichiometry), and conclude that each needs development with respect to at least one criterion. 5. We end with an initial attempt at assessing the expansion of our own contribution, the Geometric Framework, to better satisfy the criterion of ecological explicitness.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.006 | 0.015 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".