Benzoannulation of aromatic heterocycles: advances in the 21st century
Bibliographic record
Abstract
Benzoannulated aromatic heterocycles (BAHs), also known as benzoheterocycles, are key building blocks in the development of functional materials and pharmaceuticals. They are involved in a variety of biochemical processes in nature. The prevalence and widespread use of these molecules stimulates the chemical community's ongoing interest in developing methods to construct carbazole, indole, quinoline, isoquinoline and benzo[b]thiophene motifs. The most common strategy for preparing them is the heteroannulation of functionalized benzene derivatives. Over the last two decades, an alternative approach based on the annulation of heterocyclic derivatives has been developed: benzoannulation, also known as benzannulation. Compared to classical heteroannulation, this approach has several advantages and has led to significant progress in the availability of a variety of benzoheterocycles in recent years. This review is the first to analyze the development of benzoannulation methods for aromatic heterocycles in the 21st century. We highlight the advantages of the benzoannulation strategy, including the versatility of the methods, the availability of starting compounds and the ability to obtain products with specified substituents in the benzene ring. This review aims to help chemists with the synthesis of benzoheterocycles of a specific structure for various applications, ranging from the design of biologically active compounds and the synthesis of natural products to materials chemistry. The bibliography includes 298 references.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".