Iron supply to the western subarctic Pacific: Importance of iron export from the Sea of Okhotsk
Bibliographic record
Abstract
Iron is an essential nutrient and plays an important role in the control of phytoplankton growth (Martin et al., 1989). Atmospheric dust has been thought to be the most important source of iron, supporting annual biological production in the western subarctic Pacific (WSP) (Duce and Tindale, 1991; Moore et al., 2002). We argue here for another source of iron to the WSP. We found extremely high concentrations of dissolved and particulate iron in the Okhotsk Sea Intermediate Water (OSIW) and the North Pacific Intermediate Water (NPIW), and water ventilation processes in this region probably control the transport of iron through the intermediate water layer from the continental shelf of the Sea of Okhotsk to wide areas of the WSP. Additionally, our time series data in the Oyashio region of the WSP indicate that the pattern of seasonal changes in dissolved iron concentrations in the surface‐mixed layer was similar to that of macronutrients, and that deep vertical water mixing resulted in higher winter concentrations of iron in the surface water of this region. The estimated dissolved iron supply from the iron‐rich intermediate waters to the surface waters in the Oyashio region was comparable to or higher than the reported atmospheric dust iron input and thus a major source of iron to these regions. Our data suggest that the consideration of this source of iron is essential in our understanding of spring biological production and biogeochemical cycles in the western subarctic Pacific and the role of the marginal sea.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".