Using long-lived radium isotopes as water-mass tracers in the North Sea and investigating their use for tracking artificial ocean alkalinization.
Bibliographic record
Abstract
The long-lived radium isotopes, 226Ra (t1/2= 1600 yrs.) and 228Ra (t1/2 = 5.8 yrs.), are established shelf-sea tracers, capable of discerning key water-mass compositions and distribution patterns from source to sea. Within the North Sea, radium has not only been recognized as a suitable tool for identifying water-mass characteristics, but 228Ra has also been found to effectively trace total alkalinity (AT). Within the known continental shelf pump system of the North Sea, this indirect link between radium and the carbonate system has recently enticed greater interest for climate mitigation strategies, such as Artificial Ocean Alkalinization (AOA). But, prior to initiating intentional anthropogenic perturbations on the complex coastal North Sea, it is imperative to understand the initial state of the system. In order to do just that, our study builds on the previous knowledge of water-mass distributions within the North Sea, distinguishing the sources and mixing patterns which contribute to the three main water-masses (with particular focus placed on further identification of the North Atlantic input source components). Quantitatively, these patterns are further supported through the use of inverse modelling techniques, which highlight the importance of end members for each of the water-masses. Overall this study provides a more in-depth baseline understanding of water-mass distribution and mixing within the North 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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".