Subpolar eddies from high-resolution, multi-platform experiments in the Labrador Sea
Bibliographic record
Abstract
Mesoscale structures are key dynamical features of the ocean. They are associated with a variety of short-lived, small-scale processes—such as energy cascades, changes in ocean stratification, and modulation of carbon and oxygen uptake—that occur at submesoscales. In high latitudes, where mesoscale features can span only tens of kilometers, capturing submesoscale processes is especially challenging. To address this, extensive submesoscale-resolving, multiplatform experiments were conducted in the summers of 2022 and 2024 across two anticyclonic eddies in the Labrador Sea. These experiments employed two underwater electric gliders equipped with nitrate, microstructure shear, chlorophyll fluorescence, oxygen, and turbidity sensors, operated in tandem with ship-based instruments including underway CTDs, a moving vessel profiler, a thermosalinograph, ADCPs, and an X-band radar system. Surface drifters deployed within the eddies were used to track their stability, for weeks after the dedicated experiments. Observations acquired both along the peripheries and within the cores of the eddies revealed new insights into submesoscale dynamics and their biophysical feedbacks.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".