Bioavailability of Engineered Nanoparticles in Soil Systems
Bibliographic record
Abstract
Nanotechnologies form a field of research that is still emerging with major gaps in knowledge regarding the behavior and potential toxicological risks of engineered nanoparticles (ENPs) in soils. While most of the studies are conducted in porous media (quartz and glass beads) and culture media, less frequently are the studies carried out in natural soils. However, the complex interactions occurring in soils, mediated by both soil components and soil organisms, are essential in bioavailability processes. Therefore, this paper is intended to highlight particularly the bioavailability of ENPs in soils. The potential release pathways of ENPs to soils are described and are faced with a lack of specific regulation and definitive nomenclature. This paper reviews a number of studies regarding ENP toxicological bioavailability on microorganisms and microfauna, mesofauna, and macrofauna inhabiting the soil, as well as on soil-plant systems. The paper especially discusses ENP behavior in soils that affect ENP bioavailability to the edaphic biota. Particular attention is paid to the factors regulating these processes [i.e., (1) ENP-dependent factors, (2) soil properties, and (3) soil components], focusing on organic matter.
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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".