Ice Drift in the Beaufort Sea from Tracking Beacons, Winter 2009-2010
Bibliographic record
Abstract
Abstract In the winter of 2009-2010, seven ice tracking beacons were deployed in two separate arrays in the ExxonMobil/Imperial Oil lease known as Ajurak in the Canadian sector of the Beaufort Sea. The Ajurak lease lies 100 to 160 km north of the Mackenzie Delta, in water depths ranging from 60 m to 600 m. The purpose of the deployment was to assess the fate of a hypothetical under-ice well blow-out. The purpose of this paper is to describe the planning process prior to field operations including a Health, Safety and Environmental (HSE) plan and a Safe Operations Plan (SOP), the deployment, the data analysis and the resulting drift tracks and velocity statistics. Satellite imagery was used to monitor ice conditions prior to deployment to assess the competence of the ice cover, and also to chart the development of land fast ice throughout the winter. An array of beacons deployed in early December followed the expected pattern of westerly drift with periods of rapid drift and occasional reversals and stationary periods. The leading beacon passed Point Barrow, 750 km west of Ajurak, in 4 months. By July, this beacon had drifted well into the Chukchi Sea, a total of 1370 km from its deployment location. The second array of beacons, deployed in mid-January, remained within the Canadian Beaufort Sea. The longest surviving beacon in this array drifted about 200 km west of Ajurak and stopped reporting in late April. Drift of this array appeared to be impeded by the development of large seaward extensions in the land fast ice adjacent to the Alaskan coast, as well as a series of onshore movements of the polar pack ice.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".