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Record W1988660034 · doi:10.1080/10916466.2010.495960

The Comparison of Bitumens from Oil Sands with Different Recovery Profiles

2012· article· en· W1988660034 on OpenAlexaff
John R. Woods, Judy Kung, David Kingston, T. McCracken, Luba S. Kotlyar, B.D. Sparks, Patrick H. J. Mercier, Siauw Ng, Kevin Moran

Bibliographic record

VenuePetroleum Science and Technology · 2012
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsSyncrude (Canada)National Research Council Canada
Fundersnot available
KeywordsAsphalteneAsphaltOil sandsChemistryViscositySulfurNitrogenSolventCarbon fibersChromatographyComposition (language)Materials scienceOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

It has been proposed that, regardless of origin, the recovery of bitumen from oil sands is related to its viscosity. Asphaltene and resin contents are known to affect the viscosity of bitumen. In this article we compare the composition of solvent-extracted bitumens from several Athabasca oil sands with very different recovery profiles. After careful removal of any associated mineral matter by ultra-centrifugation, each bitumen sample was separated into saturate, aromatic, resin, and asphaltene (SARA) fractions by an enhanced SARA technique. The individual components were then characterized by several complementary analytical techniques, including carbon, nitrogen, nitrogen, sulfur, size exclusion chromatography molecular weight (MWn) plus proton and 13C nuclear magnetic resonance spectroscopy. Based on this comparison, we see no correlation between the recovery of bitumen and its composition.

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 score0.004
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
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.244
Teacher spread0.235 · 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

Citations10
Published2012
Admission routes1
Has abstractyes

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