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Record W1983079594 · doi:10.1021/ma000807b

Fractionation of Cyclic Polystyrene from Linear Precursor by HPLC at the Chromatographic Critical Condition

2000· article· en· W1983079594 on OpenAlexaffabout
Hee Cheong Lee, Hyunjung Lee, Wonmok Lee, Taihyun Chang, Jacques Roovers

Bibliographic record

VenueMacromolecules · 2000
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsCitationPolystyreneComputer scienceSocial mediaLibrary scienceInformation retrievalChemistryWorld Wide WebOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

ADVERTISEMENT RETURN TO ISSUEPREVCommunication to the...Communication to the EditorNEXTFractionation of Cyclic Polystyrene from Linear Precursor by HPLC at the Chromatographic Critical ConditionHee Cheong Lee, Hyunjung Lee, Wonmok Lee, Taihyun Chang, and Jacques RooversView Author Information Department of Chemistry and Center for Integrated Molecular Systems, Pohang University of Science and Technology, Pohang, 790-784, Korea Institute for Chemical Process and Environmental Technology, National Research Council of Canada, Ottawa, Ontario K1A 0R9, Canada Cite this: Macromolecules 2000, 33, 22, 8119–8121Publication Date (Web):October 14, 2000Publication History Received9 May 2000Revised8 September 2000Published online14 October 2000Published inissue 1 October 2000https://pubs.acs.org/doi/10.1021/ma000807bhttps://doi.org/10.1021/ma000807brapid-communicationACS PublicationsCopyright © 2000 American Chemical SocietyRequest reuse permissionsArticle Views1751Altmetric-Citations169LEARN 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:Chromatography,Fractionation,Polymers,Precursors,Size exclusion chromatography 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)0.001
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: none
Teacher disagreement score0.035
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0350.032

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 head0.005
GPT teacher head0.246
Teacher spread0.241 · 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

Citations179
Published2000
Admission routes2
Has abstractyes

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