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Record W4292241901 · doi:10.1007/s13668-022-00436-x

The Endocannabinoid System and Eating Behaviours: a Review of the Current State of the Evidence

2022· review· en· W4292241901 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Nutrition Reports · 2022
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsMcGill University
FundersGovernment of Canada
KeywordsEndocannabinoid systemHuman studiesCannabinoid receptorClinical nutritionFood intakeMedicinePsychologyReceptorEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.669
Threshold uncertainty score0.719

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.079
GPT teacher head0.395
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it