Applications of α-Keto Carbocations in Carbon-Carbon and Carbon-Nitrogen Bond Formation
Bibliographic record
Abstract
This thesis describes synthetic applications of α-keto carbocations, which represent potentially useful, but poorly studied, reversed polarity equivalents of enolates.\nIn the first chapter, a Ag(I) – mediated method for the nucleophilic displacement of α-halocarbonyl compounds to construct carbon-carbon bonds is described. The highly electrophilic nature of the putative α-keto carbocation intermediates enables the use of relatively unreactive nucleophiles in both intra- and intermolecular contexts. Such intermediates also present interesting opportunities for stereocontrol: our efforts to carry out diastereoselective additions to chiral α-keto carbocations are described.\nOxazoles are an important class of heterocycles, and several syntheses are addressed in Chapter 2. Our approach to this class of compounds employs a TMSOTf mediated Ritter reaction to construct the carbon-nitrogen bond. Cycloaddition of 2-alkoxyoxazoles with alkynes presents a facile route for furan synthesis.\nThe final chapter describes our attempts to apply anion-π interaction in organocatalysis. These interactions between anions and electron-deficient arenes have been characterized in some detail and have recently been applied in ion transport. Applications of prolinol-based secondary amines incorporating electron-deficient aromatic groups are described.
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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) | 0.003 | 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".