Density and Viscosity of Athabasca Bitumen, a Condensate Sample, and Mixtures Applicable for Expanding-Solvent Steam-Assisted-Gravity-Drainage and Liquid-Addition-to-Steam-for-Enhancing-Recovery Processes
Bibliographic record
Abstract
Summary This paper presents the density and viscosity measurements for a condensate sample, Athabasca bitumen, and Athabasca bitumen/condensate mixtures applicable for in-situ bitumen-recovery methods and pipeline transportation. The measurements for the densities and viscosities are reported at different temperatures (ambient to 200°C) and pressures (atmospheric to 10 MPa). For mixtures, a wide range of solvent fractions (5-50 wt%) is investigated. The data for the mixtures are also evaluated with predictive schemes as well as with correlation models representing certain mixing rules proposed in the literature. The results indicate that mixture densities are well represented by the excess-volume method, with an average absolute relative deviation (AARD) of 0.78%. The Bij model predicts the mixture viscosities with an AARD of 11.7%.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".