MétaCan
Menu
Back to cohort
Record W4235144018 · doi:10.1201/b11962-28

Wettability of fine solids extracted from bitumen froth

2014· book-chapter· en· W4235144018 on OpenAlexaboutno aff
Fei Chen, J.A. Finch, Zhenghe Xu, Jan Czarnecki

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsAsphaltWettingMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Oil sands deposits in northern Alberta contain more hydrocarbons than all OPEC reserves combined. The amount recoverable using the existing technology is slightly larger than the total oil reserves of Saudi Arabia. Today, the total production of oil from oil sands amounts to over 20% of Canadian oil consumption, threequarters of which is from open pit mining; the remainder comes from in situ recovery. Clark’s hot water extraction process and its modifications have been used to separate bitumen from the oil sand ore. In this process, the mined oil sand is mixed with hot water and the digested slurry is fed into large gravity separation vessels, where bitumen is recovered as a froth product in a process similar to flotation. The froth produced as such typically contains ca. 60% bitumen, 30% water, and 10% solids. The froth is cleaned by adding a diluent (an organic liquid mixture, such as naphtha) to provide a density difference between the water and hydrocarbon phases and to reduce the viscosity of the froth. The diluted bitumen is then fed through a two-stage centrifuge (at ca. 250 x and 2500 x g, respectively) to remove coarse particles in the first stage by scroll machines and the remaining fine solids and finely dispersed water droplets in the second stage by disc centrifuges. (Inclined plate settlers and/or third-stage centrifuges are also used in commercial operations.) Collectively called froth treatment, this process produces a product still containing ~ 2% water and 0.5% solids.

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 score0.346
Threshold uncertainty score0.689

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
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 head0.017
GPT teacher head0.219
Teacher spread0.202 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same topicAsphalt Pavement Performance EvaluationFrench-language works237,207