Getting to the bottom of feeding behaviour: who’s on top?
Bibliographic record
Abstract
Traditionally there has been a tendency to focus on peripheral "bottom-up" feeding-related signals and their resulting downstream actions on hypothalamic centers when studying the feeding behaviour of animals. A problem with this hierarchal approach emerges especially with respect to acquiring a human model attempting to explain what is ultimately a distributed control of feeding and energy balance. This review focuses on illuminating the means by which we have come to understand the complexities of feeding, and takes the next step in an attempt to propose a distinctive top-down view of this composite behaviour. It is argued that in evolutionary terms humans demonstrate behaviours unique to all species as represented by an expanded forebrain and the resultant psychological "non-homeostatic" mediators of feeding. Emphasis is placed on a distributionist "two-tier" model, arguing that traditional short-term (cholescystokinin, ghrelin, peptide YY, glucagon-like peptide 1, etc.) and long-term (insulin and leptin) feeding signals may be actively suppressed by the nested nuclei and projections of cortical-limbic brain areas. It is the motivational state (dependent on depletion-repletion signals of hunger and satiety) that in turn has the capability to modulate how rewarding or how palatable a food item may be perceived; thus, both sides of the two-tiered model of feeding behaviour are complimentary and interdependent all at once. In the end, this paper is both commentary and critical review. This synthesis purports that as evolutionary processes spawned consciousness, the psychology of hunger and the present-day discordance of gene-environment interaction forever changed the feeding behaviour of Homo sapiens.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".