Export of nutrients from the Arctic Ocean
Bibliographic record
Abstract
Abstract This study provides the first physically based mass‐balanced transport estimates of dissolved inorganic nutrients (nitrate, phosphate, and silicate) for the Arctic Ocean. Using an inverse model‐generated velocity field in combination with a quasi‐synoptic assemblage of hydrographic and hydrochemical data, we quantify nutrient transports across the main Arctic Ocean gateways: Davis Strait, Fram Strait, the Barents Sea Opening (BSO), and Bering Strait. We found that the major exports of all three nutrients occur via Davis Strait. Transports associated with the East Greenland Current are almost balanced by transports associated with the West Spitsbergen Current. The most important imports of nitrate and phosphate to the Arctic occur via the BSO, and the most important import of silicate occurs via Bering Strait. Oceanic budgets show that statistically robust net silicate and phosphate exports exist, while the net nitrate flux is zero, within the uncertainty limits. The Arctic Ocean is a net exporter of silicate (−15.7 ± 3.2 kmol s −1 ) and phosphate (−1.0 ± 0.3 kmol s −1 ; net ± 1 standard error) to the North Atlantic. The export of excess phosphate (relative to nitrate) from the Arctic, calculated at −1.1 ± 0.3 kmol s −1 , is almost twice as large as previously estimated. Net transports of silicate and phosphate from the Arctic Ocean provide 12% and 90%, respectively, of the net southward fluxes estimated at 47 ° N in the North Atlantic. Additional sources of nutrients that may offset nutrient imbalances are explored, and the relevance and the pathway of nutrient transports to the North Atlantic are discussed.
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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 | 0.001 | 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".