Asymmetric Synthesis with Organoselenium Compounds – The Past Twelve Years
Bibliographic record
Abstract
The discovery and synthetic applications of novel organoselenium compounds and their reactions proceeded rapidly during the past fifty years and such processes are now carried out routinely in many laboratories. At the same time, the growing demand for new enantioselective processes provided new challenges. The convergence of selenium chemistry and asymmetric synthesis led to key developments in the 1970s, although the majority of early work was based on stoichiometric processes. More recently, greater emphasis has been placed on greener catalytic variations, along with the discovery of novel reactions and a deeper understanding of their mechanisms. The present review covers the literature in this field from 2010 to early 2023 and encompasses asymmetric reactions mediated by chiral selenium-based reagents, auxiliaries, and especially, catalysts. Protocols based on achiral selenium compounds in conjunction with other species of chiral catalysts, as well as reactions that are controlled by chiral substrates, are also included.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".