Using radium and carbon isotopes to evaluate the biogeochemical impact of boundary exchanges in the North Sea
Bibliographic record
Abstract
The North Sea is one of the most studied coastal regions on the planet,yet inputs of carbon and nutrients from the boundaries of the system remain an area of uncertainty in for both the observational and numerical modeling communities alike. Diagenetic reactions within sediments and subsequent sediment-water column exchange provide inputs of dissolved inorganic carbon (DIC), alkalinity (AT) and nutrients (NO3-, PO43-) to the water column throughout the North Sea. In the shallow parts of the North Sea, additional sedimentary inputs from mudflats combined with freshwater inputs from the adjacent European landmass provide a substantial input of dissolved constituents into the Southern North Sea. This study aims to explore the biogeochemical impacts of such boundary exchanges in the North Sea using an extensive suite of water column samples collected in September, 2011. The dominant controls of the stable carbon isotope signature of DIC (δ13CDIC) are determined and isolated. These include in-situ biological activity,and land-based signals, which can affect the paleo records found ins helf sediment cores. These investigations can guide modelling studies to assess the impacts of changing river loads on the biogeochemistry of coastal waters. The sediments and the coastline are also a well-defined source of Radium isotopes (224Ra, 223Ra, 228Ra). The dispersion of longer-lived 228Ra into the North Sea from the coastline can be used to calculate the offshore transport of numerous carbon, nutrient and metal species. Meanwhile the seafloor provides the dominant source of 224Ra, thus a strong relationship between Ra and Alkalinity provides a signature of sedimentary AT release.
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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".