Cross‐Isobath Freshwater Exchange Within the North Atlantic Subpolar Gyre
Bibliographic record
Abstract
Abstract The amount of cross‐isobath freshwater exchange within the North Atlantic subpolar gyre is estimated from numerical modelling simulations. A regional configuration of the Nucleus for European Modelling of the Ocean model is used to carry out three simulations with horizontal resolutions of 1/4°, 1/12°, and 1/4° with a 1/12° nested domain. Freshwater transport is calculated across five isobaths in six regions for three distinct water masses. Fresh Polar Water is only transported offshore from the western coast of Greenland and the southern coast of Labrador; other regions have onshore transport of freshwater or little offshore transport. The salty water masses of Irminger and Labrador Sea Water typically have onshore transport, acting to promote subsurface freshening of the Labrador Sea. The freshwater transport via the Polar Water mass experiences a large degree of seasonal variability, while the Irminger and Labrador Sea Water masses do not. Decomposing the freshwater transport into the mean and turbulent components indicates that most regions and water masses have stronger freshwater transport associated with the mean flow while the turbulent flow in often the opposite direction. The only water mass and region where the mean and turbulent freshwater transport act in the same direction is Polar Water along the western margin of Greenland. Model resolution plays an important role in determining cross‐isobath exchange as our results from an identically forced simulation at 1/4° has reduced seasonal cycles, reduced transport, and sometimes transport in the opposite direction when compared against the 1/12° resolution simulations.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".