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Record W4412557708 · doi:10.59761/rcr5163

Benzoannulation of aromatic heterocycles: advances in the 21st century

2025· article· en· W4412557708 on OpenAlexaff
Iumzhana A. Bolotova, Alexey M. Kavun, Валерий З. Ширинян, Andrey G. Lvov

Bibliographic record

VenueRussian Chemical Reviews · 2025
Typearticle
Languageen
FieldChemistry
TopicChemical Synthesis and Reactions
Canadian institutionsCentre in Green Chemistry and Catalysis
Fundersnot available
KeywordsChemistry

Abstract

fetched live from OpenAlex

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. <br>The bibliography includes 298 references.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.665
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.285
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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