Balancing New Approaches and Harmonized Techniques in Nano- and Microplastics Research
Bibliographic record
Abstract
ADVERTISEMENT RETURN TO ISSUEEditorialNEXTBalancing New Approaches and Harmonized Techniques in Nano- and Microplastics ResearchDenise M. Mitrano*Denise M. MitranoDepartment of Environmental Systems Science, ETH Zurich, Universitatstrasse 16, 8092 Zurich, Switzerland*[email protected]More by Denise M. MitranoView Biographyhttps://orcid.org/0000-0001-8030-6066, Miriam L. DiamondMiriam L. DiamondDepartment of Earth Sciences, University of Toronto, Toronto M5S 3B1, CanadaSchool of the Environment, University of Toronto, Toronto M5T 1P5, CanadaMore by Miriam L. Diamond, Jae-Hong KimJae-Hong KimDepartment of Chemical and Environmental Engineering, Yale University, New Haven, Connecticut 06520-8292, United StatesMore by Jae-Hong Kim, Kam Chiu TamKam Chiu TamDepartment of Chemical Engineering, Waterloo Institute for Nanotechnology, University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2L 3G1, CanadaMore by Kam Chiu Tam, Min YangMin YangResearch Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 18 Shuangqing Road, Haidian District, Beijing 100084, ChinaMore by Min Yang, and Zhanyun WangZhanyun WangSwiss Federal Laboratories for Materials Science and Technology (EMPA), Technology and Society Laboratory, 9014 St. Gallen, SwitzerlandMore by Zhanyun WangCite this: ACS EST Water 2023, 3, 8, 1972–1975Publication Date (Web):June 7, 2023Publication History Received30 May 2023Published online7 June 2023Published inissue 11 August 2023https://doi.org/10.1021/acsestwater.3c00282Copyright © 2023 American Chemical SocietyRequest reuse permissions This publication is free to access through this site. Learn MoreArticle Views496Altmetric-Citations-LEARN 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 PDF (2 MB) Get e-AlertscloseSUBJECTS:Computer simulations,Environmental pollution,Plastics,Testing and assessment,Toxicity 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 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 | 0.001 | 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 | 0.000 | 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".