Base-catalyzed C-alkylation of potassium enolates with styrenes <i>via</i> a metal–ene reaction: a mechanistic study
Bibliographic record
Abstract
Base-catalyzed, C-alkylation of potassium (K) enolates with styrenes (CAKES) has recently emerged as a highly practical and convenient method for elaboration or synthesis of pharmaceutically-relevant cores. K enolate-type precursors such as alkyl-substituted heterocycles (pyridines, pyrazines and thiophenes), ketones, imines, nitriles and amides undergo C-alkylation reactions with styrene in the presence of KOtBu or KHMDS. Surprisingly, no studies have probed the reaction mechanism beyond the likely initial formation of a K enolate. Herein, a synergistic approach of computational (DFT), kinetic and deuterium labelling studies rationalizes various experimental observations and supports a metal-ene-type reaction for amide CAKES. Moreover, our approach explains experimental observations in other reported C-alkylation reactions of other enolate-type precursors, thus implicating a general mechanism for CAKES.
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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) | 0.001 | 0.000 |
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".