MétaCan
Menu
Back to cohort
Record W2136261414 · doi:10.1002/cjce.5450820414

A New Device to Determine Bitumen Extraction from Oil Sands

2004· article· en· W2136261414 on OpenAlexafffundvenue
Manoj Luthra, Robert J.G. Lopetinsky, R. Sean Sanders, K. Nandakumar, Jacob H. Masliyah

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsSyncrude (Canada)University of Alberta
FundersSyncrude
KeywordsAsphaltOil sandsSlurryExtraction (chemistry)Environmental sciencePetroleum engineeringPulp and paper industryGeotechnical engineeringGeologyMaterials scienceEngineeringEnvironmental engineeringChemistryChromatographyComposite material

Abstract

fetched live from OpenAlex

Abstract The Batch Extraction Unit (BEU) has been in use since the 1970's for studying the extraction of bitumen from oil sand. The present study investigates an alternative method for estimating bitumen recovery, based on visualization of oil sand slurry undergoing digestion. A Couette flow device is loaded with known amounts of oil sand and water. Air is bubbled through the oil sand slurry, while it is subjected to controlled chemical conditions and shear environment. Images of the slurry are captured at various time intervals and then analyzed using image analysis software, which selects black areas based on the gray scale intensities of the area in view. The variation of the black area with time is used as a measure of bitumen recovery. The technique provides quick estimates of final recovery, while enabling kinetic studies of the liberation and recovery processes. The experimental set‐up offers great flexibility in selecting conditions for the digestion of oil sands.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.204
Teacher spread0.195 · 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

Citations8
Published2004
Admission routes3
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicEnhanced Oil Recovery TechniquesFrench-language works237,207