Aggregates in Paraffinic Froth Treatment: Settling Properties and Structure
Bibliographic record
Abstract
The settling rate of aggregates formed during paraffinic froth treatment depends strongly on process conditions. This work examined the influences of process temperature, solvent-to-bitumen ratio (S/B), and type of solvent used on the settling rate. Experiments were performed at temperatures ranging from 30 to 90 °C and various S/Bs, using isopentane, n- pentane, and n- hexane as paraffinic solvents. Based on studies of the settling rate, two factors can be emphasized. First, process temperature has the greatest influence on the settling rate of aggregates. Second, for a given solvent and temperature, increasing S/B results in an increase of the settling rate. Study of the aggregates formed during paraffinic froth treatment allowed for better understanding of the phenomena affecting the settling rate. Besides developing an aggregate sampling method based on solubility parameters, experimental procedures for determining structural parameters were successfully applied.
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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 | 0.000 | 0.000 |
| 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".