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Correction to Molecular Characterization of Strongly and Weakly Interfacially Active Asphaltenes by High-Resolution Mass Spectrometry

2021· article· en· W3172850638 on OpenAlexfundno aff
Dewi A. Ballard, Martha L. Chacón‐Patiño, Peiqi Qiao, Kevin J. Roberts, Robert Rae, Peter J. Dowding, Zhenghe Xu, David Harbottle

Bibliographic record

VenueEnergy & Fuels · 2021
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of CanadaRoyal Academy of EngineeringNational Science Foundation
KeywordsNoticeCitationLibrary scienceInformation retrievalComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

ADVERTISEMENT RETURN TO ISSUEPREVAddition/CorrectionNEXTORIGINAL ARTICLEThis notice is a correctionCorrection to Molecular Characterization of Strongly and Weakly Interfacially Active Asphaltenes by High-Resolution Mass SpectrometryDewi A. BallardDewi A. BallardMore by Dewi A. Ballardhttps://orcid.org/0000-0002-5506-199X, Martha L. Chacón-PatiñoMartha L. Chacón-PatiñoMore by Martha L. Chacón-Patiñohttps://orcid.org/0000-0002-7273-5343, Peiqi QiaoPeiqi QiaoMore by Peiqi Qiao, Kevin J. RobertsKevin J. RobertsMore by Kevin J. Robertshttps://orcid.org/0000-0002-1070-7435, Robert RaeRobert RaeMore by Robert Rae, Peter J. DowdingPeter J. DowdingMore by Peter J. Dowding, Zhenghe XuZhenghe XuMore by Zhenghe Xu, and David Harbottle*David HarbottleMore by David Harbottlehttps://orcid.org/0000-0002-0169-517XCite this: Energy Fuels 2021, 35, 12, 10339Publication Date (Web):May 28, 2021Publication History Published online28 May 2021Published inissue 17 June 2021https://pubs.acs.org/doi/10.1021/acs.energyfuels.1c01496https://doi.org/10.1021/acs.energyfuels.1c01496correctionACS PublicationsCopyright © 2021 American Chemical Society. This publication is licensed under CC-BY. This publication is Open Access under the license indicated. Learn MoreArticle Views686Altmetric-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 (790 KB) Get e-Alertsclose 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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.206
Threshold uncertainty score0.690

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.031
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.003
Science and technology studies0.0030.001
Scholarly communication0.0040.004
Open science0.0030.002
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.2060.132

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 head0.207
Teacher spread0.203 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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