Dissolved Cd, Co, Cu, Fe, Mn, Ni, and Zn in the Arctic Ocean
Bibliographic record
Abstract
Abstract During the Polarstern (PS94) expedition, summer 2015, part of the international GEOTRACES program, sources and sinks of dissolved (D) Cd, Co, Cu, Fe, Mn, Ni, and Zn were studied in the central Arctic Ocean. In the Polar Surface Water in which the TransPolar Drift (TPD) is situated, salinity and δ 18 O derived fractions indicated a distinct riverine source for silicate DCo, DCu, DFe, DMn, and DNi. Linear relationships between DMn and the meteoric fraction depended on source distance, likely due to Mn‐precipitation during transport. In the upper 50 m of the Makarov Basin, outside the TPD core, DCo, DMn, DNi, DCd, and DCu were enriched by Pacific waters, whereas DFe seemed diluted. DCo, DFe, DMn, and DZn were relatively high in the Barents Sea and led to enrichment of Atlantic water flowing into the Nansen Basin. Deep concentrations of all metals were significantly lower in the Makarov Basin compared to the Nansen and Amundsen, the Eurasian, Basins. The Gakkel ridge hydrothermal input and higher continental slope convection are explanations for higher metal concentrations in the Eurasian Basins. Although scavenging rates are lower in the Makarov Basin compared to the Eurasian Basins, the residence time is longer and therefore scavenging can decrease the dissolved concentrations with time. This study provides a baseline to assess future change, and additionally identifies processes driving trace metal distributions. Our results underline the importance of fluvial input as well as shelf sources and internal cycling, notably scavenging, for the distribution of bio‐active metals in the Arctic Ocean.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 teacher head, 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".