Using reconstructed Irminger Water changes within the past three decades to connect the West Greenland shelf to the production of Labrador Sea Water
Bibliographic record
Abstract
In this study we analyze the exchange processes between the West Greenland shelf and the Labrador Sea. This region is affected by warm and saline waters originating from the subtropical North Atlantic, as well as cold and fresh waters from the Arctic and the Greenland Ice Sheet. Heat and freshwater both impact the local formation of Labrador Sea Water (LSW) that itself is a major contributor to the Atlantic Meridional Overturning Circulation. We use the ARMOR3D large-scale hydrographic data set from the Copernicus Marine Environmental Monitoring Service (CMEMS) and validate it with ship-based measurements in the period between 1993 to 2018. By extracting cross-shelf sections from ARMOR3D for various locations around Greenland, we reconstruct time series of local water masses like the Irminger Water (IW) for the past three decades. Previous studies from the West Greenland shelf have shown that IW properties are locally anti-correlated to changes in LSW. We analyze the interannual and decadal variability of these IW time series and compare them towards hydrographic changes observed in the interior Labrador Sea. Since ARMOR3D allows us to investigate interannual and decadal changes along cross-shelf sections, the goal of this study is to unravel the complex connection between changes in the shelf regions around Greenland and the interior Labrador Sea, especially the local water mass production.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".