Bibliographic record
Abstract
Found in cannabis, cannabidiol (CBD) holds promise as a nonpsychoactive cannabinoid in treating a number of conditions, including anxiety, schizophrenia, and some forms of epilepsy.However, large scale studies on the therapeutic use of CBD are lacking, and more research is needed to precisely establish its safety and efficacy.Extraction of CBD from cannabis is challenging, and past methods of synthesizing CBD have suffered from at least one of the following: poor selectivity, low yields, complex and laborious reaction sequences, or unavailable starting materials.We report here a concise approach to CBD synthesis from readily available nerol.This route uses directed orthometallation to regioselectively allylate olivetol dimethyl ether, followed by a biomimetic oxidative cyclization with Mn(III) to cleanly generate dimethyl CBD in low yield.We also demonstrate that using cationic polyene cyclization as the key ringforming step produces a similar yield of dimethyl CBD in a complex mixture of isomers.iii
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".