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Record W1969999555 · doi:10.2118/117677-ms

Bitumen Extraction from Oil Sands Ore-Water Slurry Using CaO (Lime) and/or Ozone

2008· article· en· W1969999555 on OpenAlex
Tayfun Babadagli, Zvonko Burkus, Speros E. Moschopedis, B. Özüm

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Thermal Operations and Heavy Oil Symposium · 2008
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Alberta
FundersSyncrudeShell Canada
KeywordsOil sandsSlurryAsphaltExtraction (chemistry)LimeOzonePulp and paper industryWaste managementMetallurgyEnvironmental scienceMaterials scienceChemistryEnvironmental engineeringComposite materialChromatography

Abstract

fetched live from OpenAlex

Abstract Bitumen extraction efficiency is increased in oil sands ore-water slurry based extraction process by increasing solubility of naturally occurred asphaltic acids by addition of CaO (lime) and/or by oxidation of bitumen asphaltenes by Ozone (O3) to surfactant species, at as low as 35 °C temperature. Experimental findings suggest that a non-caustic bitumen extraction process (i.e. without using NaOH as extraction process aid) could be used commercially by conditioning the oil sands ore-water slurry with CaO and/or Ozone, which would allow high extraction efficiencies at about 35 °C temperature, reduce energy consumption and CO2 emission for the extraction of bitumen and eliminate the accumulation of Na+ ions in the recycled release water. Further tests are on-going to provide sufficient data for the commercial implementation of the use of CaO and/or Ozone at oil sands-ore water slurry based extraction plants.

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 score0.333
Threshold uncertainty score0.572

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.258
Teacher spread0.240 · 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