Causes of a Vessel Navigation Disruption Event in Pack Ice on the Umiak I During March 29-31, 2016
Bibliographic record
Abstract
Pack ice pressure events and heavily deformed shear zone and land-fast ice conditions can cause serious disruption to vessel navigation through ice-infested waters, resulting in operational delays and increased costs due to downtime. Understanding the causes behind ice-related vessel navigation disruption events is critical to efforts to build predictive models for such events. These models will help offshore operators prepare for and avoid such events, thus decreasing downtime, lowering operational costs, and improving safety. This paper examines a three-day period during which operations of the Umiak I, an ice-strengthened vessel owned and operated by Fednav Limited, were repeatedly disrupted by extreme ice conditions in the shear zone offshore Voisey’s Bay, Labrador. During March 29–31, 2016, the Umiak I was unable to make significant progress through the 9–10/10ths concentration ice in the shear zone and land-fast ice east of Voisey’s Bay, and engaged in prolonged backing and ramming maneuvers in order to break through the pack. This study examines the regional metocean factors during the two months prior which led to the extreme conditions in the shear zone and caused the vessel navigation disruption event.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".