Targeting the endocannabinoid system for gastrointestinal diseases: future therapeutic strategies
Bibliographic record
Abstract
Cannabinoids extracted from the marijuana plant (Cannabis sativa) and synthetic cannabinoids have numerous effects on gastrointestinal (GI) functions. Recent experimental data support an important role for cannabinoids in GI diseases. Genetic studies in humans have proven that defects in endocannabinoid metabolism underlie functional GI disorders. Mammalian cells have machinery, the so-called endocannabinoid system (ECS), to produce and metabolize their own cannabinoids in order to control homeostasis of the gut in a rapidly adapting manner. Pharmacological manipulation of the ECS by cannabinoids, or by drugs that raise the levels of endogenous cannabinoids, have shown beneficial effects on GI pathophysiology. This review gives an introduction into the functions of the ECS in the GI tract, highlights the role of the ECS in GI diseases and addresses its potential pharmacological exploitation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".