Catalytic Homogeneous Asymmetric Hydrogenation: Successes and Opportunities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This is an overview of successes in the realm of catalytic homogeneous asymmetric hydrogenation of substrates primarily of interest in the synthesis of pharmaceuticals in order to identify important problems still unsolved. First, tables are provided that list the successful reductions to over 90% enantiomeric excess of prochiral ketones to alcohols, imines to amines, and olefins to saturated carbon centers. Noted in the tables are the metal (including “green” metals Mn, Fe, and Co) or enzyme, the class of ligand, the conditions of the medium, and the scale of reduction, if over 1 kg of product, as well as the nature of the process, whether direct hydrogenation using H2 gas (DH), transfer hydrogenation (TH), or hydrogenation with dynamic kinetic resolution (DKR). Tables of representative pharmaceutical or fine chemicals products are provided for each class of substrate. With this overview, the opportunities for further research and development become clearer.
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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 | 0.000 | 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 | 0.000 | 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) | 0.002 | 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 it