MétaCan
Menu
Back to cohort
Record W4409531590 · doi:10.1038/s41467-025-58313-4

Bis-indole chiral architectures for asymmetric catalysis

2025· article· en· W4409531590 on OpenAlexafffund
Junshan Lai, Benjamin List, Jolene P. Reid

Bibliographic record

VenueNature Communications · 2025
Typearticle
Languageen
FieldChemistry
TopicAxial and Atropisomeric Chirality Synthesis
Canadian institutionsUniversity of British Columbia HospitalUniversity of British Columbia
FundersAlliance de recherche numérique du CanadaNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaGovernment of CanadaCompute Canada
KeywordsEnantioselective synthesisTsuji–Trost reactionCatalysisHydroborationCombinatorial chemistryIndole testNanotechnologyChemistryOrganocatalysisFlexibility (engineering)Computer scienceOrganic chemistryMaterials scienceMathematics

Abstract

fetched live from OpenAlex

Chiral scaffolds are essential to the advancement of asymmetric synthesis, yet the development of privileged motifs that more effectively communicate asymmetry constitutes a grand challenge for chemists. Here we describe a method using a confined chiral Brønsted acid catalyst to combine two inexpensive and widely available materials-indole and acetone-into a class of C₂-symmetric, spirocyclic compounds called SPINDOLE. SPINDOLEs extend the versatility of established frameworks by offering greater flexibility and ease of synthesis. The resulting chiral compounds can be readily modified to create diverse structures that excel in promoting highly selective reactions such as hydrogenation, allylic alkylation, hydroboration, and Michael addition. This work introduces a powerful strategy for advancing asymmetric catalysis, enabling the creation of versatile chiral frameworks with broad synthetic potential.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.014
GPT teacher head0.302
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicAxial and Atropisomeric Chirality SynthesisFrench-language works237,207