Li-Zn-Pb multi isotopic characterization of the Loire River Basin, France
Bibliographic record
Abstract
The Loire River in France is approximately 1010 km long and drains an area of 117 800 km2. Upstream, the Loire River flows following a south to north direction from the Massif Central down to the city of Orléans, 650 km from its source. The Loire River is one of the main European riverine inputs to the Atlantic Ocean. Over time, its basin has been exposed to numerous sources of anthropogenic metal pollutions, such as metal mining, industry, agriculture and domestic inputs. The Loire River basin is thus an excellent study site to develop new isotope systematics for tracking anthropogenic sources of metal pollutions (Zn and Pb) and also to investigate Li isotope tracing that can provide key information on the nature of weathering processes at the Loire River Basin scale. Preliminary data show that Li-Zn-Pb concentrations and isotopic compositions span a wide range in river waters of the Loire River main stream and the main tributaries. There is a clear contrast between the headwaters upstream and rivers located downstream in the lowlands. In addition, one of the major tributaries within the Massif Central (the Allier River) is clearly influenced by inputs resulting from mineralizations and thermomineral waters. The results showed that, on their own, each of these isotope systematics reveals important information about the geogenic or anthropogenic origin Li-Zn-Pb. Considered together, they are however providing a more integrated understanding of the overall budgets of these elements at the scale of the Loire River Basin.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".