HOW TO MODEL WATER-IN-OIL EMULSION FORMATION
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT Water-in-oil mixtures were grouped into four states or classes: stable, mesostable, unstable, and entrained water. Only stable and mesostable states can be characterized as emulsions. These states were established according to lifetime, visual appearance, complex modulus, and differences in viscosity. Water-in-oil emulsions made from crude oils have different classes of stability as a result of the asp haltene and resin contents, as well as differences in the viscosity of the starting oil. In this paper a new numerical modelling scheme is proposed and is based on empirical data and the corresponding physical knowledge of emulsion formation. The density, viscosity, saturate, asphaltene and resin contents are used to compute a class index which yields either an unstable or entrained water-in-oil state or a meso-stable or stable emulsion. A prediction scheme is given to estimate the water content and viscosity of the resulting water-in-oil state and the time to formation with input of wave-height.
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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 | 0.001 |
| 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 it