Bibliographic record
Abstract
Recent studies have provided evidence that the endocannabinoid (EC) system has very significant effects on energy balance and metabolism through the central control of appetite and by affecting peripheral metabolism. Endocannabinoids are endogenous phospholipid derivatives which bind and activate cannabinoid receptors type 1 and type 2 (CB1 and CB2 receptors). The CB1 receptor, a G-protein coupled receptor, is believed to be responsible for the majority of the central effects of endocannaboids on appetite. Chronic positive energy balance and obesity have been associated with an overactivation of the endocannaboid system which has been suggested to contribute to the development of abdominal obesity and to associated metabolic abnormalities which increase the risk of cardiovascular disease and type 2 diabetes. Animal studies had shown that stimulation of the cannabinoid CB1 receptor with endocannaboids such as anandamide could induce first an increase in food intake leading to body weight gain. Furthermore, an exciting development in this field has been the discovery of CB1 receptors in many peripheral tissues, including key organs involved in carbohydrate and lipid metabolism such as the adipose tissue and liver. Thus, blocking CB1 receptors located in the liver and adipose tissue could have an additional impact on the metabolic risk profile beyond what could be explained by the reduction in food intake and the related body weight loss. Preclinical studies have shown that rimonabant, the first CB1-receptor blocker to be available in clinical practice, could not only induce a reduction in food intake, but could also produce body weight loss beyond what could be explained by its effect on food intake. Thus, the evidence from preclinical studies have suggested that CB1 blockade could represent a relevant approach to reduce food intake, to induce body weight loss, and, most importantly, to "fix" the dysmetabolic state of viscerally obese patients at increased cardiometabolic risk.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".