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Record W2239624870 · doi:10.1002/cjce.22374

Phase behaviour of sesame (<i>Sesamum indicum L</i>.) seed oil using supercritical CO<sub>2</sub>

2015· article· en· W2239624870 on OpenAlexaffvenue
Andresa Carla Feihrmann, Willyan Machado Giufrida, Marleny D.A. Saldaña, Jéssica de Carvalho Lima, Leandro Ferreira‐Pinto, José Rafael Santos Botelho, Vladimir Ferreira Cabral, Raul Nunes de Carvalho, Marcos L. Corazza, Lúcio Cardozo‐Filho

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2015
Typearticle
Languageen
FieldChemistry
TopicFree Radicals and Antioxidants
Canadian institutionsUniversity of Alberta
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsSesamumSupercritical fluidvan der Waals forceThermodynamicsChemistryBubble pointPhase transitionVan der Waals equationEquation of statePhase (matter)Binary systemAnalytical Chemistry (journal)ChromatographyBubbleBinary numberOrganic chemistryMathematicsPhysics

Abstract

fetched live from OpenAlex

ABSTRACT New experimental data were measured for phase transition of the binary system CO 2 + black sesame oil. A variable volume cell was employed using the static synthetic method in a temperature range of 303–333 K, pressures up to 20 MPa, and CO 2 mass fractions between 0.12–0.39 g/g. For mass fractions &gt; 0.39, phase transition data were not measured due to pressure limitations of the high‐pressure system used. Vapour‐liquid transitions (VLE) of bubble point (BP) were determined. Phase transition data of CO 2 + black sesame oil were compared to reported data from the literature involving CO 2 and similar oils. The trend of the phase transition behaviour between all systems compared was similar. Phase equilibrium data obtained experimentally were successfully modelled with the Peng‐Robinson equation of state (PR‐EoS) combined with the van der Waals mixing rule (PR‐vdW2) and Wong‐Sandler mixing rule (PR‐WS).

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 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 score0.005
Threshold uncertainty score0.669

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 integrity0.0000.001
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 head0.020
GPT teacher head0.238
Teacher spread0.218 · 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 teacher head, 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

Citations10
Published2015
Admission routes2
Has abstractyes

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