Assessment of long-term fate of metals in soils: Inferences from analogues
Bibliographic record
Abstract
The assessment of the health and environmental impacts of metal contamination in soils is complicated, and in different ways than is the assessment of many other contaminants. One of the foremost problems is that the metals are often relatively immobile, so that it is necessary to verify predictions of mobility and impact far into the future. One approach is to seek analogue information: information from studies that may not have set out to measure attributes related to metal behaviour, but that none the less provide useful insights. One example would be the information on the mobility of natural clays and pedogenic metals such as iron and aluminum in soils. It is well accepted that clay particles will move downward in soils; what is less commonly inferred is that any contaminants associated with the clays will also move downward. For mobility of some metals, this may be a dominant process. Similarly, bioturbation has proven to markedly outpace leaching for many metals. This paper considers analogues related to cesium from bomb-fallout and Chernobyl, other natural radionuclide inputs to the soil, soil pedogenesis, pollen and non-metal industrialage inputs, ancient metal works, and soil fertility management. Related to biological transfers and toxicity, it considers analogy among elements an d among biota, and analogy to ecotoxicology of metals to freshwater biota. Where possible, limiting values for parameters of assessment models have been derived. Key words: Terrestrial, leaching, mobility, ecotoxicity, assessment
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".