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Record W2005775306 · doi:10.1021/cr400615v

Small Heterocycles in Multicomponent Reactions

2014· review· en· W2005775306 on OpenAlexaffabout
Benjamin H. Rotstein, Serge Zaretsky, Vishal Rai, Andrei K. Yudin

Bibliographic record

VenueChemical Reviews · 2014
Typereview
Languageen
FieldChemistry
TopicMulticomponent Synthesis of Heterocycles
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCitationLibrary scienceChemistryComputer science

Abstract

fetched live from OpenAlex

ADVERTISEMENT RETURN TO ISSUEPREVReviewSmall Heterocycles in Multicomponent ReactionsBenjamin H. Rotstein†‡, Serge Zaretsky†, Vishal Rai†§, and Andrei K. Yudin*†View Author Information† Davenport Research Laboratories, Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, Ontario Canada, M5S 3H6‡ Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital, and Department of Radiology, Harvard Medical School, 55 Fruit Street, Boston, Massachusetts 02114, United States§ Department of Chemistry, Indian Institute of Science Education and Research (IISER) Bhopal, Indore By-pass Road, Bhauri, Bhopal 462 066, MP India*E-mail: [email protected]Cite this: Chem. Rev. 2014, 114, 16, 8323–8359Publication Date (Web):July 17, 2014Publication History Received29 October 2013Published online17 July 2014Published inissue 27 August 2014https://pubs.acs.org/doi/10.1021/cr400615vhttps://doi.org/10.1021/cr400615vreview-articleACS PublicationsCopyright © 2014 American Chemical SocietyRequest reuse permissionsArticle Views12974Altmetric-Citations779LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Aldehydes,Aziridines,Ethers,Inorganic carbon compounds,Reactivity Get e-Alerts

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0280.009

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 head0.133
GPT teacher head0.348
Teacher spread0.215 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations987
Published2014
Admission routes2
Has abstractyes

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