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Record W2948816145 · doi:10.1021/acsenergylett.9b00779

Lithium Recovery from Oil and Gas Produced Water: A Need for a Growing Energy Industry

2019· article· en· W2948816145 on OpenAlex

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 · 2019
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEnvironmental scienceFossil fuelPetroleum industryWaste managementLithium (medication)Energy (signal processing)Process engineeringChemistryPetroleum engineeringEngineeringEnvironmental engineeringPhysicsMedicine

Abstract

fetched live from OpenAlex

ADVERTISEMENT RETURN TO ISSUEPREVViewpointNEXTLithium Recovery from Oil and Gas Produced Water: A Need for a Growing Energy IndustryAmit Kumar*Amit KumarDepartment of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139-4307, United StatesDepartment of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139-4307, United States*E-mail: [email protected]More by Amit Kumarhttp://orcid.org/0000-0001-7807-3427, Hiroki FukudaHiroki FukudaDepartment of Materials Engineering, University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z4More by Hiroki Fukuda, T. Alan HattonT. Alan HattonDepartment of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139-4307, United StatesMore by T. Alan Hattonhttp://orcid.org/0000-0002-4558-245X, and John H. Lienhard V*John H. Lienhard, VDepartment of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139-4307, United States*E-mail: [email protected]More by John H. Lienhard, Vhttp://orcid.org/0000-0002-2901-0638Cite this: ACS Energy Lett. 2019, 4, 6, 1471–1474Publication Date (Web):June 5, 2019Publication History Received10 April 2019Accepted3 May 2019Published online5 June 2019Published inissue 14 June 2019https://pubs.acs.org/doi/10.1021/acsenergylett.9b00779https://doi.org/10.1021/acsenergylett.9b00779article-commentaryACS PublicationsCopyright © 2019 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 Views32299Altmetric-Citations101LEARN 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 (1 MB) Get e-AlertscloseSUBJECTS:Adsorption,Lipids,Metals,Organic polymers,Wastewater 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 score0.315
Threshold uncertainty score0.556

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 head0.007
GPT teacher head0.192
Teacher spread0.185 · 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