Bibliographic record
Abstract
In the past 10 years, the field of NHC–Pd catalysis has grown at an impressive rate. Early studies largely focussed on catalyst design for a limited number of reactions (e.g. C–C coupling reactions). However, the opportunities unveiled by these early studies initiated many and varied research efforts, and a large number of research teams are involved in the field. As a consequence, the range of reactions catalysed by NHC–Pd complexes is now substantial: in addition to the traditional C–C coupling reactions, which still remains the most comprehensively investigated field, it encompasses such reactions as direct C–H arylation, telomerisation, hydrogenation and Buchwald-Hartwig amination (to name a few). A number of catalytic systems are now active enough that they can be considered for pilot or industrial scale production in the fine chemicals and pharmaceutical industry. Yet limitations remain, in particular regarding catalyst deactivation/decomposition. In this chapter, these various aspects are critically examined, with an emphasis on catalyst design for each class of transformation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.002 |
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".