Bibliographic record
Abstract
ABSTRACT The current knowledge of the physical fate and behaviour of crude oil and petroleum products spilled in Arctic situations is reviewed. Oil in and under ice undergoes a variety of processes depending on location and environmental conditions. Modeling of oil in such environments becomes complex by the addition of these processes. Spreading was evaluated for oil on ice, under ice, in snow, in brash ice, and between blocks of ice. Oil transport under sheet and broken ice are considered, both for sea and river conditions. The movement of oil under the ice may be governed by the undersea roughness as well as the relative velocity of the water with respect to the ice. The effects of oil on a growing ice sheet are examined, both for its effects on ice formation and for the thermal effects of oil inclusions in ice. The migration of oil through ice is examined, focussing primarily on the movement through brine channels. The effects of oil on the surface of ice are considered, with emphasis on the effects of surface pools on ice melt. Similar consideration is given to the effects of oil on snow on the surface of ice. The quantitative studies of oil in open and dynamic ice conditions are reviewed. Observations of intentional small-scale spills in leads and ice fields are reviewed and compared with observations from real spills. The most common ultimate fate of oil in an ice field is release onto water. Some of the measurements made in earlier years suffered from the lack of good measurement techniques. Further research is needed to improve the understanding of oil behavior in ice-infested waters.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".