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Record W2041716611 · doi:10.1002/cjce.5450820420

Adhesion of Bitumen to a Metal Surface in a Flowing Oil Sands Slurry

2004· article· en· W2041716611 on OpenAlexaffvenue
Yuming Xu, Tadeusz Dąbroś, W. I. Friesen, Waldemar B. Maciejewski, Jan Czarnecki

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsSyncrude (Canada)Devon Energy (Canada)Natural Resources Canada
Fundersnot available
KeywordsSlurryAsphaltOil sandsMaterials scienceAdhesionMetallurgyImpellerCoatingComposite materialEngineering

Abstract

fetched live from OpenAlex

Abstract Bench‐scale experiments were conducted to study the behaviour of oil sands slurries. While a slurry was being stirred with a standard impeller, the mass of bitumen, Mad, that adhered to a steel probe dipped into the slurry was measured. Mad remained small up to a critical adhesion time, τad, and then increased rapidly. τad depended on ore grade, temperature, pH, and clay content. The implication for hydrotransport of oil sands is clear: τad should be greater than the residence time of the slurry to avoid the problem of bitumen coating the pipe wall and the attendant increase in pumping pressure.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.005
GPT teacher head0.169
Teacher spread0.164 · 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

Citations2
Published2004
Admission routes2
Has abstractyes

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