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Record W2922157348 · doi:10.1021/acs.jced.8b01163

Experimental Data and Thermodynamics Modeling (PC-SAFT EoS) of the {CO<sub>2</sub> + Acetone + Pluronic F-127} System at High Pressures

2019· article· en· W2922157348 on OpenAlexafffund
Leandro Ferreira‐Pinto, Paulo Cardozo Carvalho de Araújo, Marleny D.A. Saldaña, Pedro F. Arce

Bibliographic record

VenueJournal of Chemical & Engineering Data · 2019
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of Alberta
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoNatural Sciences and Engineering Research Council of CanadaCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsChemistryThermodynamicsAcetoneEquation of stateTernary operationPoloxamerTernary numeral systemPhase (matter)Organic chemistryPolymerCopolymer

Abstract

fetched live from OpenAlex

In this study, we reported data of phase equilibria of the ternary {CO 2 (1) + acetone (2) + pluronic F-127 (3)} system using the static synthetic method with a visual cell at temperatures ranging from 303 to 323 K, pressures near to 10 MPa, two concentrations of pluronic F-127 in acetone (0.01 g·cm –3 and 0.02 g·cm –3 ), and molar fractions varying between 0.3 to 0.9. The thermodynamic modeling using the perturbed-chain statistical associating fluid theory equation of state (PC-SAFT EoS) was capable of describing the behavior of the experimental data (liquid–vapor transitions bubble points) satisfactorily.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.219
Teacher spread0.207 · 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 designSimulation or modeling
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

Citations14
Published2019
Admission routes2
Has abstractyes

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