Hypothetical Soil Thresholds for Biological Effects of Rare Earth Elements
Bibliographic record
Abstract
Objectives: Anthropogenic exposures to rare earth elements are poorly known and there is limited information on their toxicity and ecotoxicity. At the same time, world production of rare earth elements has doubled every 15 years over the last half-century, and high environmental concentrations of gadolinium and lanthanum have already been found. The current review aims to give some estimates of overall exposures and an initial in-depth appraisal of thresholds for effects on agricultural soil. The results are envisaged to be used in initial assessments of agricultural soil where the natural concentrations have been anthropogenically enhanced. Methods: An extensive review has been made of available scientific literature. Criteria have been established for the selection and analysis of eligible research. For instance, only effects on soils with vegetation have been included in the assessment of biological effects. A species sensitivity distribution based on 25% inhibition of organism functions has been used to establish thresholds for effects on soil organisms. Results: Around the year 2000, mean anthropogenic contributions of lanthanides in European soil regions were at most a few per cent of the total soil content. Since then, they should have increased considerably. The proposed hypothetical threshold for agricultural soils is 1125 mg total rare earth element per kg of soil. This threshold is about 8 times the natural soil concentration. Conclusions: If this result holds up to scrutiny, it implies that general anthropogenic pollution by rare earth elements will not be a threat to agricultural sustainability for the coming generation. A preliminary assessment suggests that this threshold would also protect humans from adverse effects due to secondary exposure.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".