Export of newly oxygenated Labrador Sea Water at 53N
Bibliographic record
Abstract
Most of the life-sustaining oxygen found in the global deep ocean is supplied in one of only a handful of key regions around the globe, such as the Labrador Sea in the subpolar North Atlantic. Here, oxygen is supplied directly to the deep ocean during the formation of Labrador Sea Water (LSW), when convective mixing continuously brings low-oxygen deep water towards the surface and into contact with the atmosphere. The continuous exchange between the surface and deep ocean during convection can bring newly oxygenated waters as deep as 2000m. Although the associated oxygen uptake has been observed and quantified, and the resulting oxygen-rich water mass in the deep ocean is readily detected throughout the Atlantic Ocean, relatively little is known about the exact mechanisms and timing of its export out of the basin. In this talk, we will present a novel dataset of oxygen sensors deployed within the boundary current at the exit of the Labrador Sea to investigate oxygen variability in the deep ocean. This is the first time that a continuous time series of oxygen has been collected in the boundary current of the Labrador Sea, with a total of 10 sensors deployed on 4 moorings from 2016 to 2020. The sensors at 600m depth show a sudden change in oxygen, temperature, and salinity in the spring, which we discuss in relation to deep convection in the interior. We also use data from Argo floats to analyse export pathways from the convection region to the location of the moorings. Our results give new insights into how the oxygen taken up in the central Labrador Sea subsequently spreads into the global deep ocean, and lay the basis for future work on quantifying variability of oxygen transport at the exit of the Labrador Sea.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".