Experimental Determination of <i>k</i>-Values and Compositional Analysis of Liquid Phases in the Liquid–Liquid Equilibrium Study of (Athabasca Bitumen + Ethane) Systems
Bibliographic record
Abstract
Phase behavior properties of (bitumen + solvent) systems have a significant effect on surface upgrading methods and are necessary for the recovery of bitumen from reservoir. In this study, the phase partitioning and component distribution between phases as well as phase properties at equilibrium condition for the (Athabasca bitumen + ethane) system at room temperature were experimentally evaluated. The experiments were conducted using a designed pressure–volume–temperature (PVT) apparatus to obtain liquid–liquid equilibrium properties as well as extraction yield for (bitumen + solvent) systems. In addition, the equilibrium k -value for each component present in the mixture at equilibrium condition was calculated on the basis of compositional analysis of liquid phases and available correlations for the molecular weight of heavy components. The impact of pressure and solvent to bitumen ratio on the boiling point curves and compositional analysis of flashed off liquids as well as equilibrium k -values were evaluated. Finally, the molecular weight of flashed off liquid phase samples were estimated on the basis of molecular weight and compositional analysis of liquids.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".