Biogeochemical Cycling of Dissolved Zinc in the Western Arctic (Arctic GEOTRACES GN01)
Bibliographic record
Abstract
Abstract The biogeochemical cycling of dissolved zinc (dZn) was investigated in the Western Arctic along the U.S. GEOTRACES GN01 section. Vertical profiles of dZn in the Arctic are strikingly different than the classic “nutrient‐type” profile commonly seen in the Atlantic and Pacific Oceans, instead exhibiting higher surface concentrations (~1.1 nmol/kg), a shallow subsurface absolute maximum (~4–6 nmol/kg) at 200 m coincident with a macronutrient maximum, and low deep water concentrations (~1.3 nmol/kg) that are homogeneous (sp.) with depth. In contrast to other ocean basins, typical inputs such as rivers, atmospheric inputs, and especially deep remineralization are insignificant in the Arctic. Instead, we demonstrate that dZn distributions in the Arctic are controlled primarily by (1) shelf fluxes following the sediment remineralization of high Zn:C and Zn:Si cells and the seaward advection of those fluxes and (2) mixing of dZn from source waters such as the Atlantic and Pacific Oceans rather than vertical biological regeneration of dZn. This results in both the unique profile shapes and the largely decoupled relationship between dZn and Si found in the Arctic. We found a weak dZn:Si regression in the full water column (0.077 nmol/μmol, r2 = 0.58) that is higher than the global slope (0.059 nmol/μmol, r2 = 0.94) because of the shelf‐derived halocline dZn enrichments. We hypothesize that the decoupling of Zn:Si in Western Arctic deep waters results primarily from a past ventilation event with unique preformed Zn:Si stoichiometries.
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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 | 0.000 | 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".