Influence of Oil Sands Composition on Bitumen Quality During Non‐Aqueous Bitumen Extraction from the Athabasca Deposit
Bibliographic record
Abstract
ABSTRACT The aim of the present work is to identify the most important species affecting a non‐aqueous bitumen extraction process and bitumen quality. This investigation was carried out on four petrologic end member samples from Syncrude's North Mine collected in 2012 (NM12), i.e., marine claystone (MC), marine sand (MS), estuarine claystone (EC), and estuarine sand (ES). Each end member was separately mixed with cyclohexane at a ratio of 40:60 (cyclohexane:end member), and the bitumen‐cyclohexane solutions were collected at different settling times (1–30 min). These solutions were analyzed to determine the amount, particle size distribution, and mineralogical composition of suspended fine solids (SFS), water content, as well as the bitumen content using a focused beam reflectance measurement (FBRM) particle size analyzer, Karl Fischer (KF) titration, x‐ray diffraction (XRD), quantitative XRD (QXRD), and elemental analysis. The SFS was composed of mainly illite and kaolinite after cyclohexane extraction from MC, MS, EC, and ES. Although mixed layer expandable clay minerals (i.e., illite‐smectite and kaolinite‐smectite) were identified in the original clay, end members (EC and MC), illite‐smectite, and kaolinite‐smectite were not observed in the SFS of the bitumen‐cyclohexane solutions obtained from the four petrologic end members. The SFS content and bitumen quality of the bitumen product were affected slightly but significantly by the end member composition and settling time, respectively. Illite and kaolinite were identified as the main minerals in the SFS of the bitumen products after relatively long settling times.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".