Stable oxygen isotopes from the MOSAIC expedition show vertical and horizontal variability of sea-ice and river water signals in the upper Arctic Ocean during winter
Bibliographic record
Abstract
Our aim is to better understand how local winter modification and advected signals from the Siberian Shelf affect the structure of the upper Arctic Ocean along the Transpolar Drift (TPD). Hereto we use stable oxygen isotopes of the water (δ18O) in combination with salinity to quantify river water contributions (fr) and changes due to sea-ice formation or melting (fi) in the upper ~150m of the water column during the MOSAIC drift. Furthermore, ratios of fi/fr at identical salinities can be used to distinguish waters remnant from the previous summer and those modified locally.Within the ongoing winter we observed salinification and deepening of the mixed layer (ML) due to sea-ice related brine release together with interleaving waters at the base of the ML and within the main halocline. These interleaving waters with variable sea-ice and river water signals are observed for the first time and have not been observed during summer expeditions before.The MOSAIC floe drifted in and out of the freshwater-rich part of the TPD and into the Atlantic regime throughout the winter. Despite these strong regime changes the sea-ice related brine content accumulated during the ongoing winter remained visible within the water column. Budgets derived by integration of signals over the upper 100m result in ~1 to 5 m of pure sea-water (34.92 salinity and 0.3‰ δ18O) removed from the water column for ice formation and are much higher than ice thicknesses of ~0.5 to 2 m observed for the MOSAIC floe. For further evaluation scaling factors have to be considered accounting e.g. for the different densities of ice and water as well as for the lower salinity in the halocline relative to pure sea-water. Therefore, our analysis indicates a lower limit of the advected signal relative to local winter modification within the Arctic Ocean halocline.
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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 | 0.000 |
| 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".