Organoselenium‐Catalyzed Baeyer–Villiger Oxidation of α,β‐Unsaturated Ketones by Hydrogen Peroxide to Access Vinyl Esters
Bibliographic record
Abstract
Abstract By carefully screening the organoselenium pre‐catalysts and optimizing the reaction conditions, simple dibenzyl diselenide was found to be the best pre‐catalyst for Baeyer–Villiger oxidation of (E)‐α,β‐unsaturated ketones with the green oxidant hydrogen peroxide at room temperature. The organoselenium catalyst used in this reaction could be recycled and reused several times. This new method was suitable not only for methyl unsaturated ketones, but also for alkyl and aryl unsaturated ketones. Therefore, it provided a direct, mild, practical, highly functional group‐tolerant process for the chemoselective preparation of the versatile (E)‐vinyl esters from the readily available (E)‐α,β‐unsaturated ketones. A possible mechanism was also proposed to rationalize the activity of the organoselenium catalyst in the presence of hydrogen peroxide in this Baeyer–Villiger oxidation reaction. magnified image
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".