The Importance of Considering Nonfluorescent Pyrene Aggregates for the Study of Pyrene-Labeled Associative Thickeners by Fluorescence
Bibliographic record
Abstract
ADVERTISEMENT RETURN TO ISSUEPREVNoteNEXTThe Importance of Considering Nonfluorescent Pyrene Aggregates for the Study of Pyrene-Labeled Associative Thickeners by FluorescenceHoward Siu and Jean DuhamelView Author Information Institute for Polymer Research, Department of Chemistry, University of Waterloo, Waterloo, ON N2L 3G1, Canada Cite this: Macromolecules 2005, 38, 16, 7184–7186Publication Date (Web):July 9, 2005Publication History Received4 May 2005Revised7 June 2005Published online9 July 2005Published inissue 1 August 2005https://doi.org/10.1021/ma050940+Copyright © 2005 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views409Altmetric-Citations19LEARN 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 InReddit Read OnlinePDF (68 KB) Get e-AlertsSupporting Info (1)»Supporting Information Supporting Information SUBJECTS:Aromatic compounds,Fluorescence,Hydrocarbons,Oligomers,Sodium dodecyl sulfate Get e-Alerts
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".