Formation and characterization of water-in-oil emulsions: insights from simulated mesoscale oil spill tests
Bibliographic record
Abstract
Abstract Transporting oils across Canada via pipelines, rail, and tankers poses environmental risks from potential spills into waterways. Understanding how oil properties and environmental conditions influence the formation and stability of weathered water-in-oil (w/o) emulsions is critical. This study examines the spill behaviors of five oils—Hibernia Crude (HC), Alaska North Slope (ANS), Diluted Bitumen (Dilbit), Very Low Sulfur Fuel Oil (VLSFO), and Point Arguello Crude (PAC)—in saltwater under wave conditions using mesoscale spill tests. All oils exhibited rapid initial water uptake within 24 h and significant loss of light fractions due to evaporation. The resulting w/o emulsions exhibited increased density and viscosity over the 96-hour observation period. Their types and stabilities were influenced by water content and the composition of major subfractions remaining in the emulsions. These findings underscore the importance of understanding oil-specific properties and weathering processes to predict emulsion behavior and inform effective spill response strategies.
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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".