Defining the “Ice Shed” of the Arctic Ocean's Last Ice Area and Its Future Evolution
Bibliographic record
Abstract
Abstract Sea ice will persist longer in the Last Ice Area (LIA), north of Canada and Greenland, than elsewhere in the Arctic. We combine earth system model ensembles with a sea‐ice tracking utility (SITU) to explore sources of sea ice (the “ice shed”) to the LIA under two scenarios: continued high warming (HW) rates and low warming (LW) rates (mean global warming below ca. 2°C) through the 21st century. Until mid‐century, the two scenarios yield similar results: the primary ice source shifts from the Russian continental shelves to the central Arctic, mobility increases, and mean ice age in the LIA drops from about 7 years to less than one. After about 2050, sea ice stabilizes in the LW scenario, but continues to decline in the HW scenario until LIA sea ice is nearly entirely seasonal and locally formed. Sea ice pathways through the ice shed determine LIA ice conditions and transport of material, including biota, sediments, and pollutants (spilled oil and industrial or agricultural contaminants have been identified as potential hazards). This study demonstrates that global warming has a dramatic impact on the sources, pathways and ages of ice entering the LIA. Therefore, we suggest that maintaining ice quality and preserving ice‐obligate ecologies in the LIA, including the Tuvaijuittuq Marine Protected Area north of Nunavut, Canada, will require international governance. The SITU system used in this study is publicly available as an online utility to support researchers, policy analysts, and educators interested in past and future sea ice sources and trajectories.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".