Comment on egusphere-2025-2029
Bibliographic record
Abstract
Abstract. The Northwest Passage through the Canadian Arctic Archipelago (CAA) provides a shorter transit route connecting the Atlantic Ocean to the Pacific Ocean but ever-present sea ice has prevented its practical navigation. Sea ice area in the northern route of the Northwest Passage on September 30, 2024 fell to a minimum of 4x103 km2, the lowest ice area observed since 1960. Here, we investigate the processes responsible for the record low sea ice area in 2024 and show it was driven by a perfect sequence of thermodynamic and dynamic forcing events acting on an increasingly less resilient ice cover. Specifically, multi-year ice (MYI) only made up ~10 % of total sea ice area at the start of the melt season that was characterized by an atmospheric circulation pattern that brought warm southerly air directly into the middle of CAA. This resulted in a record summer air temperature anomaly of 2.1 ℃ that drove rapid melt and limited the import of ice from higher latitude regions to 50 % of the 2016–2024 mean. Finally, positive air temperature anomalies upwards of 12 ℃ persisted into October, extending the melt season further and delaying freeze-up by 1-month, compared to the 1991–2020 baseline. Overall, a series of specific and cascading thermodynamic and dynamic processes is required to melt all ice in the northern route of Northwest Passage as it did in 2024, therefore ice conditions along this route will likely continue to remain highly variable during the transition to a summertime sea ice free Arctic.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.012 | 0.007 |
| Insufficient payload (model declined to judge) | 0.416 | 0.261 |
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".