Dearomatization–Rearomatization Strategy for Palladium-Catalyzed C–N Cross-Coupling Reactions
Bibliographic record
Abstract
Abstract Substituted aromatic compounds play important roles in materials, biological agents, dyes, etc. Thus, the synthesis of substituted aromatic compounds has been a hot topic throughout the history of organic chemistry. Traditionally, the Friedel–Crafts reaction was a powerful tool for synthesizing substituted aromatic compounds. In recent decades, metal-catalyzed cross-coupling reactions were well developed via carbon–heteroatom bond cleavage, however, having difficulties towards some strong bonds, such as C(Ar)–OH. To overcome such challenges, newer strategies are needed. In this review, we summarize the recent efforts in the development of dearomatization–rearomatization strategy for cross-coupling reactions via C(Ar)–O bond cleavage. 1 Introduction 2 Dearomatization–Rearomatization Strategy for Cross-Coupling of Phenols 3 Dearomatization–Rearomatization Strategy for Cross-Coupling of Biphenols 4 Dearomatization–Rearomatization Strategy for Cross-Coupling of Diphenyl Ethers 5 Dearomatization–Rearomatization Strategy for Cross-Coupling of Indoles 6 Summary
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; 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".