Decadal Variability Shown by the Arctic Ocean Hydrochemical Data and Reproduced by an Ice-Ocean Model
Bibliographic record
Abstract
The Arctic is experiencing a significant warming trend as well as a decadal oscillation. The atmospheric circulation represented by the Polar Vortex and the sea ice cover show decadal variabilities, while it has been difficult to reveal the decadal oscillation from the ocean interior. The recent distribution of Russian hydrochemical data collected from the Arctic Basin provides useful information on ocean interior variabilities. Silicate is used to provide the most valuable data for showing the boundary between the silicate-rich Pacific Water and the opposite Atlantic Water. Here, it is assumed that the silicate distribution receives minor influence from seasonal biological productivity and Siberian Rivers outflow. It shows a clear maximum around 100m depth in the Canada Basin, along with a vertical gradient below 100 m, which provides information on the vertical motion of the upper boundary of the Atlantic Water at a decadal time scale. The boundary shifts upward (downward), as realized by the silicate reduction (increase) at a fixed depth, responding to a more intense (weaker) Polar Vortex or a positive (negative) phase of the Arctic Oscillation. A coupled ice-ocean model is employed to reconstruct this decadal oscillation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".