Radium 228 and Radium 226 in surface water of the Kara Sea and Laptev Sea
Bibliographic record
Abstract
The surface water in the Transpolar Drift in the Arctic Ocean has a strong signature of 228Ra. In an earlier study of 228Ra in the open Arctic we showed that the major 228Ra source had to be in the Siberian shelf seas, but only a single shelf station was published so far. Here we investigate the sources of this signal on the Siberian shelves by measurements of 228Ra and 226Ra in surface waters of the Kara and Laptev Sea, including the Ob, Yenisey and Lena estuaries.In the Ob and Lena rivers we found an indication for a very strong and unexpected removal of both isotopes in the early stage of estuarine mixing, presumably related to flocculation of organic-rich material. Whereas 226Ra behaves conservatively on the shelf, the distribution of 228Ra is governed by large inputs on the shelves, although sources are highly variable. In the Kara Sea the maximum activity was found in the Baydaratskaya Bay, where tidal resonance and low freshwater supply favour 228Ra accumulation. The Laptev Sea is a stronger source for 228Ra than the Kara Sea. Since a large part of Kara Sea water flows through the Laptev Sea, the 228Ra signal in the Transpolar Drift can be described as originating on the Laptev shelf.The combined freshwater inputs from the Eurasian shelves thus produce a common radium signature with a 228Ra/226Ra activity ratio of 4.0 at 20% river water. The radium signals of the individual Siberian rivers and shelves cannot be separated, but their signal is significantly different from the signal produced on the Canadian shelf (Smith et al., in press). In this respect, the radium tracers add to the information given by Barium. Moreover, with the 5.8 year half-life of 228Ra, they have the potential to serve as a tracer for the age of a water mass since its contact with the shelves.
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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 | 0.001 |
| 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".