Enantioselective Cyclopropanation Using Dioxaborolane Ligands
Bibliographic record
Abstract
Enantiopure cyclopropanes are important subunits found in several natural products. This chapter will highlight our efforts to design a stoichiometric chiral additive for the enantioselective cyclopropanation of allylic alcohols (Eq 1). Some preliminary mechanistic features of the cyclopropanation reaction in the presence of dioxaborolane 1 and related analogs will also be presented. I. Synthesis The chiral dioxaborolane 1 can be prepared using either one of two procedures. Originally, this dioxaborolane was generated under dehydrating conditions by using two readily available precursors: N, N, N', N '-tetramethyl-L-tartaramide 2 and butylboronic acid 3 (Eq 2). These two precursors are commercially available, or easily prepared from tartaric acid (in the case of the tartaramide ( 44 )) and from butyl magnesium bromide and trimethyl borate (in the case of the butylboronic acid ( 45 )). It is not that convenient to store alkylboronic acids since these compounds are quite oxygen-sensitive. Indeed, 3 is gradually oxidized to generate
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".