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Record W2313146178 · doi:10.1021/ef201457m

Process for Solvent Extraction of Bitumen from Oil Sand

2011· article· en· W2313146178 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.

Bibliographic record

VenueEnergy & Fuels · 2011
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsOil sandsNaphthaAsphaltSolventFiltration (mathematics)Extraction (chemistry)HydrocarbonTailingsLight crude oilPulp and paper industryAsphalteneSynthetic crudeChemistryPetroleum engineeringEnvironmental scienceWaste managementChemical engineeringMaterials scienceUnconventional oilChromatographyGeologyMetallurgyFossil fuelOrganic chemistryComposite materialCatalysis

Abstract

fetched live from OpenAlex

Water-based bitumen extraction technology from mineable oil sands faces major challenges of high water usage and tailings disposal. In the present study, a process for solvent extraction of bitumen from Athabasca oil sands was investigated. In this process, oil sand is mixed with light hydrocarbon solvents, and the solvent–bitumen solution is separated from the mineral solids by centrifugal filtration or regular pressure filtration. The solvent left in the filtration cake is recovered by evaporation under vacuum at room temperature. The results show that, for both high-grade and low-grade ores, using appropriate solvent, the bitumen recovery and product quality are comparable to those from the currently used hot water extraction followed by naphtha froth treatment. The recovery of light hydrocarbon solvent is relatively easy, so this novel process has great potential to reduce solvent losses compared to existing technologies.

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 score0.052
Threshold uncertainty score0.724

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)0.0010.000

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 head0.025
GPT teacher head0.262
Teacher spread0.237 · 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