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Record W2563353782 · doi:10.1021/acsenergylett.6b00604

Electrochemical Energy Storage and Conversion at EEST2016

2016· article· en· W2563353782 on OpenAlex
Liang Li, Xueliang Sun, Jiujun Zhang, Jun Lü

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueACS Energy Letters · 2016
Typearticle
Languageen
FieldChemical Engineering
TopicMolten salt chemistry and electrochemical processes
Canadian institutionsWestern University
Fundersnot available
KeywordsElectrochemistryElectrochemical energy storageEnergy storageElectrochemical energy conversionMaterials scienceEnergy transformationEnvironmental scienceProcess engineeringEngineering physicsChemistryEngineeringSupercapacitorPhysicsElectrodePower (physics)Thermodynamics

Abstract

fetched live from OpenAlex

ADVERTISEMENT RETURN TO ISSUEPREVEnergy FocusNEXTElectrochemical Energy Storage and Conversion at EEST2016Liang Li*†, Xueliang Andy Sun‡, Jiujun Zhang§, and Jun Lu*∥View Author Information† College of Physics, Optoelectronics and Energy, Center for Energy Conversion Materials & Physics (CECMP), Soochow University, Suzhou 215006, People's Republic of China‡ Department of Mechanical and Materials Engineering, University of Western Ontario, London, Ontario, Canada N6A 5B9§ College of Science, Shanghai University, 99 Shangda Road, Shanghai 200444, China∥ Chemical Sciences and Engineering Division, Argonne National Laboratory, Argonne, Illinois 60439, United States*E-mail: [email protected] (L.L.).*E-mail: [email protected] (J.L.).Cite this: ACS Energy Lett. 2017, 2, 1, 151–153Publication Date (Web):December 15, 2016Publication History Received15 November 2016Accepted5 December 2016Published online15 December 2016Published inissue 13 January 2017https://pubs.acs.org/doi/10.1021/acsenergylett.6b00604https://doi.org/10.1021/acsenergylett.6b00604article-commentaryACS PublicationsCopyright © 2016 American Chemical Society. This publication is available under these Terms of Use. Request reuse permissions This publication is free to access through this site. Learn MoreArticle Views1605Altmetric-Citations5LEARN 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 (4 MB) Get e-AlertscloseSUBJECTS:Batteries,Electrical energy,Electrodes,Energy density,Materials 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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.004
GPT teacher head0.175
Teacher spread0.172 · 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