Advances in Solid Phase Microextraction and Perspective on Future Directions
Bibliographic record
Abstract
ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTAdvances in Solid Phase Microextraction and Perspective on Future DirectionsNathaly Reyes-GarcésNathaly Reyes-GarcésDepartment of Chemistry, University of Waterloo, Ontario, Canada N2L 3G1More by Nathaly Reyes-GarcésView Biography, Emanuela GionfriddoEmanuela GionfriddoDepartment of Chemistry, University of Waterloo, Ontario, Canada N2L 3G1More by Emanuela GionfriddoView Biography, German Augusto Gómez-RíosGerman Augusto Gómez-RíosDepartment of Chemistry, University of Waterloo, Ontario, Canada N2L 3G1More by German Augusto Gómez-RíosView Biography, Md. Nazmul AlamMd. Nazmul AlamDepartment of Chemistry, University of Waterloo, Ontario, Canada N2L 3G1More by Md. Nazmul AlamView Biographyhttp://orcid.org/0000-0002-6442-3569, Ezel BoyacıEzel BoyacıDepartment of Chemistry, Middle East Technical University, Ankara 06800, TurkeyMore by Ezel BoyacıView Biography, Barbara BojkoBarbara BojkoDepartment of Pharmacodynamics and Molecular Pharmacology, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 85-067 Bydgoszcz, PolandMore by Barbara BojkoView Biography, Varoon SinghVaroon SinghDepartment of Chemistry, University of Waterloo, Ontario, Canada N2L 3G1More by Varoon SinghView Biography, Jonathan GrandyJonathan GrandyDepartment of Chemistry, University of Waterloo, Ontario, Canada N2L 3G1More by Jonathan GrandyView Biography, and Janusz Pawliszyn*Janusz PawliszynDepartment of Chemistry, University of Waterloo, Ontario, Canada N2L 3G1*Phone: +1 519 888 4641. Fax: +1 519 746 0435. E-mail: [email protected]More by Janusz PawliszynView Biographyhttp://orcid.org/0000-0002-9975-5811Cite this: Anal. Chem. 2018, 90, 1, 302–360Publication Date (Web):November 8, 2017Publication History Published online8 November 2017Published inissue 2 January 2018https://doi.org/10.1021/acs.analchem.7b04502Copyright © 2017 American Chemical SocietyRIGHTS & PERMISSIONSACS AuthorChoiceArticle Views19709Altmetric-Citations440LEARN 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 PDF (11 MB) Get e-AlertsSupporting Info (1)»Supporting Information Supporting Information SUBJECTS:Coating materials,Computer simulations,Desorption,Extraction,Fibers 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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.034 | 0.018 |
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 source (direct Gemma or distilled Codex), 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".