The <sup>226</sup> Ra–Ba relationship in the North Atlantic during GEOTRACES-GA01
Bibliographic record
Abstract
Abstract. We report detailed sections of radium-226 (226Ra, T1∕2 = 1602 years) activities and barium (Ba) concentrations determined in the North Atlantic (Portugal–Greenland–Canada) in the framework of the international GEOTRACES program (GA01 section – GEOVIDE project, May–July 2014). Dissolved 226Ra and Ba are strongly correlated along the section, a pattern that may reflect their similar chemical behavior. Because 226Ra and Ba have been widely used as tracers of water masses and ocean mixing, we investigated their behavior more thoroughly in this crucial region for thermohaline circulation, taking advantage of the contrasting biogeochemical patterns existing along the GA01 section. We used an optimum multiparameter (OMP) analysis to distinguish the relative importance of physical transport (water mass mixing) from nonconservative processes (sedimentary, river or hydrothermal inputs, uptake by particles and dissolved–particulate dynamics) on the 226Ra and Ba distributions in the North Atlantic. Results show that the measured 226Ra and Ba concentrations can be explained by conservative mixing for 58 and 65 % of the samples, respectively, notably at intermediate depth, away from the ocean interfaces. 226Ra and Ba can thus be considered conservative tracers of water mass transport in the ocean interior on the space scales considered here, namely, on the order of a few thousand kilometers. However, regions in which 226Ra and Ba displayed nonconservative behavior and in some cases decoupled behaviors were also identified, mostly at the ocean boundaries (seafloor, continental margins and surface waters). Elevated 226Ra and Ba concentrations found in deepwater in the West European Basin suggest that lower Northeast Atlantic Deep Water (NEADWl) accumulates 226Ra and Ba from sediment diffusion and/or particle dissolution during transport. In the upper 1500 m of the West European Basin, deficiencies in 226Ra and Ba are likely explained by their incorporation in planktonic calcareous and siliceous shells, or in barite (BaSO4) by substitution or adsorption mechanisms. Finally, because Ba and 226Ra display different source terms (mostly deep-sea sediments for 226Ra and rivers for Ba), strong decoupling between 226Ra and Ba were observed at the land–ocean boundaries. This is especially true in the shallow stations near the coasts of Greenland and Newfoundland where high 226Ra ∕ Ba ratios at depth reflect the diffusion of 226Ra from sediment and low 226Ra ∕ Ba ratios in the upper water column reflect the input of Ba associated with meteoric waters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".