A Framework for Integrating Life-Safety and Environmental Consequences into Conventional Arctic Shipping Risk Models
Bibliographic record
Abstract
The International Code for Ships Operating in Polar Waters (Polar Code) was adopted by the International Maritime Organization (IMO) and entered into force on 1 January 2017. It provides a comprehensive treatment of topics relevant to ships operating in Polar regions. From a design perspective, in scenarios where ice exposure and the consequences of ice-induced damage are the same, it is rational to require the same ice class and structural performance for such vessels. Design requirements for different ice class vessels are provided in the Polar Code. The Polar Operational Limit Assessment Risk Indexing System (POLARIS) methodology provided in the Polar Code offers valuable guidance regarding operational limits for ice class vessels in different ice conditions. POLARIS has been shown to well reflect structural risk, and serves as a valuable decision support tool for operations and route planning. At the same time, the current POLARIS methodology does not directly account for the potential consequences resulting from a vessel incurring ice-induced damage. While two vessels of the same ice class operating in the same ice conditions would have similar structural risk profiles, the overall risk profile of each vessel will depend on the magnitude of consequences, should an incident or accident occur. In this paper, a new framework is presented that augments the current POLARIS methodology to model consequences. It has been developed on the premise that vessels of a given class with higher potential life-safety, environmental, or socio-economic consequences should be operated more conservatively. The framework supports voyage planning and real-time operational decision making through assignment of operational criteria based on the likelihood of ice-induced damage and the potential consequences. The objective of this framework is to enhance the safety of passengers and crews and the protection of the Arctic environment and its stakeholders. The challenges associated with establishing risk perspectives and evaluating consequences for Arctic ship operations are discussed. This methodology proposes a pragmatic pathway to link ongoing scientific research with risk-based methods to help inform recommended practices and decision support tools. Example scenarios are considered to illustrate the flexibility of the methodology in accounting for varied risk profiles for different vessel types, as well as incorporating input from local communities and risk and environmental impact assessments.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".