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Recent developments using malononitrile in ultrasound-assisted multicomponent synthesis of heterocycles

2023· review· en· W4390134822 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueUltrasonics Sonochemistry · 2023
Typereview
Languageen
FieldChemistry
TopicMulticomponent Synthesis of Heterocycles
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMalononitrileContext (archaeology)Scope (computer science)ReagentChemistryBiochemical engineeringReaction conditionsCombinatorial chemistryComputer scienceNanotechnologyOrganic chemistryMaterials scienceCatalysisEngineering

Abstract

fetched live from OpenAlex

Ultrasonic irradiation serves as a vigorous and environmentally sustainable approach for augmenting multicomponent reactions (MCRs), offering benefits such as thermal enhancement, agitation, and activation, among others. Malononitrile emerges as a versatile reagent in this context, participating in a myriad of MCRs to produce structurally diverse heterocyclic frameworks. This review encapsulates the critical role of malononitrile in the sonochemical multicomponent synthesis of these heterocyclic structures. The paper further delves into the biochemical and pharmacological implications of these heterocycles, elucidating their reaction mechanisms as well as delineating the method's scope and limitations. We furnish an overview of the merits and challenges inherent to this synthetic approach and offer insights for potential avenues in future research.

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.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.746
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.108
GPT teacher head0.342
Teacher spread0.234 · 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