Attempted enantiotopic group selective cyanohydrin formation from α-alkoxy aldehydes by double stereodifferentiation
Bibliographic record
Abstract
Enantiotopic group selectivity can result from the competition between substrate and reagent double stereodifferentiation. We have examined this approach for enantioselective hydrocyanation of racemic α-alkoxy aldehydes (e.g., 2-(phenylmethoxy)heptanal (1)). Reaction of 1 with TMSCN mediated by chiral nonracemic alkoxy Ti(IV) reagents under conditions known to be reasonably enantioface selective in reactions with achiral aldehydes, proceeded with very low enantiotopic group selectivity (<2:1). It was established that TMSCN can react with Ti(IV) reagents to produce "TiCN" adducts that are capable of hydrocyanation but with low substrate-controlled diastereoselectivity in reactions with 1. The poor enantiotopic group selectivity observed can be rationalized to result from this low diastereoselectivity despite the respectable levels of enantioface selectivity associated with these reagents in hydrocyanation of achiral aldehydes. Highly diastereoselective hydrocyanation of α-alkoxy aldehydes can be achieved with TMSCN in the presence of excess MgBr2·OEt2. High diastereoselectivity was also observed using achiral and chiral TiCN adducts in place of TMSCN. Although the putative TiCN adducts obtained from nonracemic alkoxy Ti(IV) reagents are implicated in enantioface selective hydrocyanation, these reagents were not enantiotopic group selective under these conditions and showed no evidence of double stereodifferentiation. The use of nonracemic bisoxazoline ligands for Mg(II) was also ineffective.Key words: cyanohydrin, 2-alkoxyalkanal, double stereodifferentiation, enantiotopic group selective reaction, kinetic resolution.
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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) | 0.001 | 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) | 0.001 | 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".