Ventilation and oxygen export in the Labrador Sea
Bibliographic record
Abstract
The Labrador Sea is one of the few regions where ventilation can replenish oxygen to the deep ocean, owing to wintertime deep convection that occurs primarily in the center of the basin. While some recent studies have aided in quantifying the amount of oxygen taken up during Labrador Sea Water (LSW) formation, less is known about how different spreading pathways of LSW contribute to the export of oxygen. In this study, we use oxygen data from the 53N mooring array in the boundary current at the exit of the Labrador Sea, together with Argo float data, in order to investigate the connection between deep convection, spreading of LSW, and oxygen export. We find that the annual cycle of the oxygen concentration is driven largely by an increased input of newly formed LSW into the boundary current in the spring and summer. The resulting oxygen increase is a result of a fast, direct southward pathway of LSW, and we estimate that the associated oxygen export accounts for about half of the uptake in the interior. The 4-year record that is presently available also indicates that the strength of the oxygen export varies interannually, which may be related to changing convection patterns. Overall, our results highlight the important role that the Labrador Sea plays in supplying oxygen to the deep ocean, and represent a first step towards better understanding the ventilation pathways out of this critical region.
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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 | 0.001 | 0.001 |
| 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".