Evaluating Navigational Information and Data Needs to Support Safe Shipping in Canadian Arctic Waters
Bibliographic record
Abstract
Abstract Vessel operators in the Canadian Arctic rely on accurate weather, water, ice, and climate (WWIC) information to make safe navigational decisions, particularly where sea ice is present. Despite the necessity of accurate WWIC information, it is currently unknown what services are being accessed by users on vessels in the Canadian Arctic, and to what extent user needs are being met by available WWIC services. User perspectives are crucial for developing meaningful WWIC services, yet there remains a gap between what service providers believe to be useful information and what users need and use for their decision-making. To address this gap, a mixed-methods online survey targeted individuals who use WWIC information while navigating in the Canadian Arctic onboard marine vessels of various sizes and types (e.g., general cargo vessels, pleasure craft, cruise ships). The results show that the needs of most respondents (61%) were met “frequently” by current WWIC services, but 63% said that their voyages would benefit from additional information and better services. Sea ice concentration was the most important WWIC factor identified to support safe navigation, followed by sea ice age/thickness, wind speed, wind direction, and then sea ice drift. The southern route of the Northwest Passage and the Arctic Ocean north of Ellesmere Island were consistently identified as areas where information was regularly inaccurate and where improvements are needed. Some of the recommended improvements for WWIC service delivery included the need for more frequent information updates, improving internet connectivity speed and satellite coverage, and more information offered in low-bandwidth formats. Significance Statement The purpose of this study is to better understand what weather, water, ice, and climate (WWIC) information vessel operators identify as a need to safely travel in the Canadian Arctic. This is important because vessel operators rely on accurate and accessible WWIC information for making safe navigation decisions, yet their needs are not always considered when creating WWIC services. Our results highlight what WWIC services are currently being used in the Canadian Arctic and make recommendations on what improvements are needed to support safe shipping in the region.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".