The relationship between the 0°C isotherm and atmospheric forcing in the Arctic Ocean
Bibliographic record
Abstract
Empirical Orthogonal Function (EOF) analysis was performed on the gridded data of the depth to the 0°C isotherm to better understand Atlantic layer variability in the Arctic Ocean. The first mode accounts for 51% of the total variance. The second mode accounts for 26% of the variance, and shows high variability in the region of inflow from the Barents Sea, and large but oppositely signed variability in the region near the Canadian Archipelago and along the path of the Transpolar Drift. This second mode is correlated with the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) indices. Composite analyses of the data using the AO and NAO indices to partition the data reinforces the physical relationship between the second EOF and atmospheric forcing. This study shows that the variability of the Atlantic Layer characterized by the 0°C isotherm across the Arctic Ocean is significantly correlated with atmospheric driving.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".