Application of the POLARIS methodology to historic ice-class ship operations in freshwater lake ice
Bibliographic record
Abstract
The primary objective of this work is to examine ship operations in freshwater versus sea ice in the context of evaluating appropriate regulatory guidelines, through analysis of historic data for the North American (Laurentian) Great Lakes region, a heavily trafficked freshwater waterway that is crucial for the functioning of Canada’s industrial heartland. The first goal of this analysis was to characterize expected ice conditions that could be found within the region through aggregating and sampling data from Canadian Ice Service ice charts over the 10-year study period, which includes the ice seasons from 2010 to 2019. This was followed by an analysis of ship traffic in the region during the same period through the use of historical archived AIS data. Lastly, the POLARIS methodology, an internationally accepted means of guiding ship operators in specific sea ice conditions, was applied to the historic ship operations described by the available AIS data to provide a comparison of historic operator decisions in lake ice to existing guidelines for operations in sea ice of similar thickness and concentration. The characterization of the regional ice conditions during the studied period was intended to provide additional context for the ship traffic analysis for comparison against typical local ice conditions along shipping routes. As existing reviewed literature previously indicated, this analysis clearly affirmed that there is significant year-to-year variability in the potential severity and duration of a given ice season in the Great Lakes. Results obtained from the analysis of historic ship traffic in the region and the application of the POLARIS methodology to this data provided valuable insights into the nature of current ship operations in ice in the Great Lakes. Overall, the trends observed suggest that current practices are well aligned with POLARIS guidelines for sea ice (89% of ice operations are in positive RIO values) and that risk mitigating measures currently used in the Great Lakes (such as icebreaker support and speed reductions when transiting through ice) are compatible with the approaches recommended in POLARIS. However, it is recommended that a more detailed analysis of the correlation between historical ship operations and icebreaking activity in specific regions be conducted to provide a better understanding of the degree to which ships operate in managed ice conditions. Further exploration of the POLARIS guidelines in the context of adapting mitigating measures into operational guidance for freshwater ice is also recommended, given the known differences in material properties of sea ice versus freshwater ice. Since it is not evident how such differences in ice types would translate into differences between the current POLARIS method and a modified “Freshwater POLARIS”, additional research is needed to assess the impact of differences in ice properties in terms of potential for ship damage and appropriate speed limits, as well as assessing the need for possible modification of Risk Index Values for lake ice types. In summary, the results of this work do suggest that the development of specifically tailored POLARIS-like guidelines presents a promising approach to aid ship operations in lake ice conditions similar to that found within the Laurentian Great Lakes during the studied 10-year period. The potential to codify current best-practices for shipping operations in the Great Lakes into such a modified method would help ensure consistency in the assessment of operational capabilities and limitations for different classes of vessels operating in lake ice. This in turn would provide greater clarity regarding expected mitigating measures and would help support effective decision-making relating to ship operations in ice.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".