Simulating dispersion of oils from a subsea release comparing mechanical and chemically enhanced dispersion — An experimental study of the influence of oil properties
Bibliographic record
Abstract
The main objective with subsea mechanical dispersion (SSMD) is to influence the fate of an oil spill in the marine environment by significantly reducing oil droplet sizes from subsea release of oil. Earlier studies have indicated that the capability of SSMD to reduce oil droplet sizes is comparable to subsea dispersant injection (SSDI). Earlier testing of SSMD has mainly used a low viscus paraffinic oil. Focus for this study was to study SSMD and SSDI effectiveness using five oil types spanning out a wide variation of relevant oil properties. Effectiveness was quantified as the reduction in oil droplet sizes measured by a Silhouette camera. Testing of the two technologies were completed in the same experiment on a simulated subsea release. The results show a variation in effectiveness for both technologies as a function of oil properties. SSMD and SSDI showed comparable effectiveness for all oils tested.
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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 | 0.001 |
| 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".