The continent-to-ocean transfer of rare earth elements in a mediterranean setting: natural processes and anthropogenic emissions
Bibliographic record
Abstract
Despite the ecological and geochemical importance of coastal and estuarine ecosystems, the continental inputs and anthropogenic emissions of trace elements in their global marine budgets are not well constrained due to a lack of comprehensive and inclusive assessment of diverse sources. Here, we investigated two small but representative rivers (Las and Eygoutier) of the Mediterranean Sea to determine the contributions of rare earth elements (REEs) from terrestrial loadings, atmospheric depositions, and anthropogenic emissions within the watersheds and Toulon Bay (France). Both the dissolved and particulate loadings of the rivers significantly increased during intermittent flood conditions relative to base flow. The flow-weighted mean concentrations of dissolved Nd (as a representative REE) ranged from 29 ± 6 and 41 ± 16 ng L −1 for the two rivers repectively, while the time-weighted mean particulate concentrations (TWMC) were 8.0 ± 3.4 and 18.8 ± 6.3 mg kg −1 . Similarly, TWMCs of atmospheric depositions were 13.3 ± 1.8 and 23.7 ± 4.0 mg kg −1 for dry and wet conditions. Atmospheric depositions and fluvial particulate loadings are the primary input and output within the watershed, while river dissolved fluxes, porewater diffusion, and atmospheric depositions are the primary external sources of Nd to the water column. Furthermore, we observed significant La anomalies in the dissolved and atmospheric fractions while the discharge of treated wastewater is a significant REE input to the bay, marked by Tb anomalies. Overall, these results suggest considering small but typical rivers, rather than focusing solely on major fluvial systems, to gain a more comprehensive understanding of the transport and fate of REEs at the continent-to-ocean interface.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".