Monitoring the Settling of Water−Solids−Asphaltenes Aggregates Using In-Line Probe Coupled with a Near-Infrared Spectrophotometer
Bibliographic record
Abstract
Zone settling develops when bitumen emulsions are treated with aliphatic solvents at solvent-to-bitumen (S/B) ratios that are higher than a critical value. Near-infrared (NIR) spectroscopy is used in combination with an in-line fiber-optic diffuse transflectance probe to monitor the settling of the water−solids−asphaltenes aggregates in solvent-diluted bitumen. NIR spectra are obtained via the probe that is inserted in the settler, and the settling rate is calculated using the acquired NIR spectroscopic data. It was observed that a lighter aliphatic solvent leads to a much higher settling rate than a heavier aliphatic solvent at the same S/B dilution ratio. For the same solvent, a higher dilution ratio results in a higher settling rate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".