MétaCan
Menu
Back to cohort
Record W2331907728 · doi:10.1021/ef5019884

Volumetric Properties of Athabasca Bitumen +<i>n</i>-Hexane Mixtures

2014· article· en· W2331907728 on OpenAlexafffund
Mohammad Kariznovi, Hossein Nourozieh, Jalal Abedi

Bibliographic record

VenueEnergy & Fuels · 2014
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaConocoPhillipsDevon Energy CorporationChevron
KeywordsAsphaltVolume (thermodynamics)HexaneSolventOil sandsMixing (physics)Steam-assisted gravity drainageChemistryFraction (chemistry)Mass fractionVolume fractionRelative densityAnalytical Chemistry (journal)ThermodynamicsMineralogyChromatographyMaterials scienceOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

The solvent-assisted bitumen recovery processes, such as vapor extraction (VAPEX) and expanding-solvent steam-assisted gravity drainage (ES-SAGD), are designed on the basis of the drainage of diluted oil at in situ conditions. Thus, the density of oil and its diluted mixtures is required to predict the production rate and cumulative oil recovery. In this study, the density of Athabasca bitumen and its mixtures with hexane at different mass fractions (0.05, 0.1, 0.2, 0.3, 0.4, and 0.5) has been accurately measured. The experiments were taken at temperatures changing from ambient up to 463 K and at pressures up to 10 MPa. The volume change upon mixing for the mixtures was investigated from the experimental results, and the influence of pressure, temperature, and solvent mass fraction on the volume change upon mixing and density was studied. The density data are evaluated by no volume change, excess volume, and effective liquid density calculation methods. It was found that the mixture data are well-predicted using effective liquid densities with an average absolute relative deviation (AARD) of 0.31%.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.199
Teacher spread0.190 · 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

Citations15
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueEnergy & FuelsSame topicPetroleum Processing and AnalysisFrench-language works237,207