The Endocannabinoid System and Eating Behaviours: a Review of the Current State of the Evidence
Bibliographic record
Abstract
PURPOSE OF THE REVIEW: The endocannabinoid system (ENS) has emerged as an important factor in food intake and may have implications for nutrition research. The objective of the current report is to summarise the available evidence on the ENS and eating behaviour from both animal and human studies. RECENT FINDINGS: The literature reviewed demonstrates a clear link between the ENS and eating behaviours. Overall, studies indicate that 2-arachidonoylglycerol (2-AG) and N-arachidonoylethanolamine (AEA) via cannabinoid receptor-1 (CNR1) binding may stimulate hunger and food intake while oleylethanolamide (OEA) may inhibit hunger. Mechanisms of these associations are not yet well understood, although the evidence suggests that there may be interactions with other physiological systems to consider. Most studies have been conducted in animal models, with few human studies available. Additional research is warranted among human populations into the ENS and eating behaviour. Evaluation of relationships between variation in ENS genes and dietary outcomes is an important area for investigation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".