Cannabidiol is a partial agonist at dopamine D2High receptors, predicting its antipsychotic clinical dose
Bibliographic record
Abstract
Although all current antipsychotics act by interfering with the action of dopamine at dopamine D2 receptors, two recent reports showed that 800 to 1000 mg of cannabidiol per day alleviated the signs and symptoms of schizophrenia, although cannabidiol is not known to act on dopamine receptors. Because these recent clinical findings may indicate an important exception to the general rule that all antipsychotics interfere with dopamine at dopamine D2 receptors, the present study examined whether cannabidiol acted directly on D2 receptors, using tritiated domperidone to label rat brain striatal D2 receptors. It was found that cannabidiol inhibited the binding of radio-domperidone with dissociation constants of 11 nm at dopamine D2High receptors and 2800 nm at dopamine D2Low receptors, in the same biphasic manner as a dopamine partial agonist antipsychotic drug such as aripiprazole. The clinical doses of cannabidiol are sufficient to occupy the functional D2High sites. it is concluded that the dopamine partial agonist action of cannabidiol may account for its clinical antipsychotic effects.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".