A vessel transit assessment of sea ice variability in the Western Arctic, 1969–2002: implications for ship navigation
Bibliographic record
Abstract
Recent investigations have shown reduced sea ice extents in Arctic regions and subsequently suggested that the Northwest Passage (NWP) might be able to sustain a prolonged shipping season. To date, no scientific evidence has been presented, within a ship navigation framework, to support increased marine traffic. The Arctic Ice Regime Shipping System (AIRSS) ice numeral (IN), which controls shipping activity in Canadian Arctic waters, was spatially assimilated with the Canadian Ice Service (CIS) historical digital database utilizing a geographic information system (GIS). INs provide a quantifiable framework for examining historical ice states in the context of ship navigation. Results provide a spatial and temporal assessment of ship navigation variability, within a ship transit framework from 1969 to 2002 for the western portion of the NWP. Feasible routes through the NWP experience extreme interannual variability in INs over the past 34 years. Yearly fluctuations of the IN can be attributed to the frequency of multiyear ice (MYI) encounters. The western coast of Banks Island experienced lower INs since 1991 and may be a potential barrier to completely navigating the NWP. Decreases in INs were also found to be associated with the positive signal of the arctic oscillation (AO) index. High-latitude MYI invasions into NWP shipping lanes appear be a major pitfall of future navigation routing in the face of climate warming.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".