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Record W1996209745 · doi:10.1021/cr300484s

New Advances in Separation Science for Metabolomics: Resolving Chemical Diversity in a Post-Genomic Era

2013· review· en· W1996209745 on OpenAlexaffabout
Naomi L. Kuehnbaum, Philip Britz‐McKibbin

Bibliographic record

VenueChemical Reviews · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCitationLibrary scienceSocial mediaComputer scienceDiversity (politics)World Wide WebChemistrySociology

Abstract

fetched live from OpenAlex

ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTNew Advances in Separation Science for Metabolomics: Resolving Chemical Diversity in a Post-Genomic EraNaomi L. Kuehnbaum and Philip Britz-McKibbin*View Author Information Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Canada*Address: Department of Chemistry and Chemical Biology, McMaster University, Hamilton, ON, L8S 4M1, Canada. Fax: +1-905-522-2509. E-mail: [email protected]Cite this: Chem. Rev. 2013, 113, 4, 2437–2468Publication Date (Web):March 18, 2013Publication History Received4 December 2012Published online18 March 2013Published inissue 10 April 2013https://pubs.acs.org/doi/10.1021/cr300484shttps://doi.org/10.1021/cr300484sreview-articleACS PublicationsCopyright © 2013 American Chemical SocietyRequest reuse permissionsArticle Views6508Altmetric-Citations277LEARN 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-AlertscloseSupporting Info (1)»Supporting Information Supporting Information SUBJECTS:Chromatography,Ions,Liquid chromatography-mass spectrometry,Metabolism,Metabolomics 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 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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.049
GPT teacher head0.364
Teacher spread0.316 · 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.

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

Citations348
Published2013
Admission routes2
Has abstractyes

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