Emulsion Formation Testing in the Laboratory and Ohmsett
Bibliographic record
Abstract
ABSTRACT This paper summarizes studies to determine the stability of water-in-oil emulsions in the OHMSETT tank facility and comparison with laboratory results. The OHMSETT tests were in four series. The tests were one week each in the first year and two weeks each in the second year. The first and second series consisted of 12 experiments each on 6 oils. The third series consisted of testing 9 oils through a series of 16 experiments. In the fourth set of tests, 8 oils were used in 16 experiments. Several of the experiments consisted of leaving the oils for longer periods of time. The rheological properties of the oils were measured and compared to the same oils undergoing emulsification in the laboratory. The oils and water-in-oil states produced were found to have analogous properties between the laboratory and the OHMSETT facility. Comparison of time and work factors showed that the energy in the two test conditions was similar. These tests also provide information on the kinetics and energy levels necessary to form emulsions, which is useful to oil spill modellers. These studies have confirmed previous laboratory studies that show that the stability of emulsions can be grouped into four categories: stable, unstable, meso-stable, and entrained. Water can reside in oil as ‘entrained water', in which larger droplets of water are temporarily suspended by viscous forces. These emulsions and mixtures have been distinguished by physical measures as well as visual differences.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".