Overflow water pathways in the North Atlantic
Bibliographic record
Abstract
As part of the international Overturning in the Subpolar North Atlantic Program (OSNAP), 135 acoustically-tracked deep floats were deployed to track the spreading pathways of Iceland-Scotland Overflow Water (ISOW) and Denmark Strait Overflow Water (DSOW) from 2014 to 2018. These water masses, which originate in the Nordic Seas, are transported by the deepest branch of the Atlantic Meridional Overturning Circulation (AMOC). The OSNAP floats provide the first directly-observed, comprehensive Lagrangian view of ISOW and DSOW spreading pathways throughout the subpolar North Atlantic. The collection of OSNAP float trajectories, complemented by model simulations, reveals that their pathways are (a) not restricted to western boundary currents, and (b) remarkably different from each other in character. The spread of DSOW from the Irminger Sea is primarily via the swift deep boundary currents of the Irminger and Labrador Seas, whereas the spread of ISOW out of the Iceland Basin is slower and along multiple export pathways. The characterization of these Overflow Water pathways has important implications for our understanding of the AMOC and its variability. Finally, reconstructions of AMOC variability from proxy data, involving either the strength of boundary currents and/or the property variability of deep waters, should account for the myriad pathways of DSOW and ISOW, but particularly so for the latter.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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".