Introduction to the Special Collection on the Arctic Ocean's Changing Beaufort Gyre
Bibliographic record
Abstract
Abstract The Beaufort Gyre circulation system is a central part of the Arctic climate undergoing significant change in all environmental parameters. This paper presents two decades of intensive observations in the Beaufort Gyre and then introduces the publications that comprise this special collection on the changing Beaufort Gyre. Observations spanning 2003–2024 are analyzed to characterize the Beaufort Gyre's evolving freshwater and heat content, which are related to wind forcing modulated by the presence of sea ice. Following a period of sustained freshwater and heat accumulation in the first half of the record, freshwater and heat content have been declining in recent years. Trends indicate that prevailing winds are changing such that they are becoming less effective at spinning up the gyre and accumulating freshwater. This forcing is dominating over a trend to a weakening sea‐ice pack that is less effective at spinning down the gyre. Details on the changing Beaufort Gyre are examined in the publications in this special collection, including studies on its sea ice, upper‐ocean properties, freshwater sources and content, the fundamental dynamical balances of the Beaufort Gyre, water‐mass circulation, and biogeochemistry. These studies bring new understanding of the Beaufort Gyre that is essential for accurately characterizing the Arctic climate system and informing future projections.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.016 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.069 | 0.036 |
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".