Radium in the Arctic Ocean - the 2015 GEOTRACES missions
Bibliographic record
Abstract
The Arctic Ocean is a small ocean basin surrounded by wide and shallow shelves receiving large river inputs. The radium quartet are four tracers of contact with sediments that give information on transport processes ranging in time scale from days to hundreds of years. \n228Ra (5.8 y halflife) is a good tracer for surface water circulation. New 2015 GEOTRACES (sections GN01+GN04) 228Ra data show the first full Barents Sea to Bering Strait transect with maximum activities in the Transpolar Drift. We compare the 2015 section in the central Arctic with earlier Polarstern sections in 1987/1991, 2007 and 2011 and discuss reasons for increases in maximum 228Ra activities (Kipp et al., 2017). \nThe penetration of 228Ra and its daughter 228Th to waters of intermediate depths (up to about 1500m) shows the exchange of these waters with shelf and slope sediments on the time scale of 228Ra decay. \nInput from the seafloor causes an enrichment of 228Ra and 226Ra in bottom waters. In deep waters (>2000m) of the Eurasian and Makarov basins 226Ra (1600 y halflife) accumulates to values around 16 dpm/100L or about twice the surface water concentration. \nIt has been argued that export production increases with decreasing ice cover in the Arctic (Arrigo et al., 2008). Natural radionuclides can help to quantify export production rates, but the fluxes found may depend on the time scale of the tracer used. The most commonly used tracer 234Th/238U (24 d halflife) has a memory much shorter than a season. The 210Po/210Pb (138 d; Roca-Martí et al., 2016) and 228Th/228Ra ratios (1.9 y) are alternatives on a full seasonal time scale. \n \nArrigo, K.R. et al., 2008. Geophys. Res. Lett. 35, L19603 \nKipp, L. et al., 2017. ASLO 2017 OSM abstracts \nRoca-Martí, M. et al., 2016. Journal of Geophysical Research: Oceans 121, 5030-5049
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".