Eddy diffusivities estimated from observations in the Labrador Sea
Bibliographic record
Abstract
Eddy diffusivities in the Labrador Sea (LS) are estimated from deep eddy resolving float trajectories, moored current meter records, and satellite altimetry. A mean residence time of 248 days in the central LS is observed with several floats staying for more than 2 years. By applying a simple random walk diffusion model, the observed distribution of float residence times in the central LS could be explained by a mean eddy diffusivity of about 300 m2 s−1. Estimates from float trajectories themselves and from moored current meter records yield significantly higher eddy diffusivities in the central LS of 950–1100 m2 s−1. This discrepancy can be explained by an inhomogeneity of the eddy diffusivity at middepth with high/low values in the central LS/region between central LS and deep Labrador Current, which could be conjectured from the mean altimetric eddy kinetic energy (EKE) distribution. The different diffusivities explain both (1) a fast lateral homogenization of water masses in the central LS and (2) a weak exchange between central LS and boundary current. The mean Lagrangian length scale of 11.5 ± 0.7 km as estimated from deep float trajectories is only slightly larger than the mean Rossby radius of deformation (8.8 km). Largest eddy diffusivities within the central LS are associated with strong eddy drifts, rather than with large swirl velocities and associated large EKE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".