The impact of engineered cobalt, iron, nickel and silver nanoparticles on soil bacterial diversity under field conditions
Bibliographic record
Abstract
Our understanding of how engineered nanoparticles (NPs) migrate through soil and affect microbial communities is scarce. In the current study we examined how metal NPs, including those from the iron triad (iron, cobalt and nickel), moved through pots of soil maintained under winter field conditions for 50 days, when mesophilic bacteria may not be dividing. Based on total metal analysis, cobalt and nickel were localized in the top layer of soil, even after exposure to high precipitation and freeze–thaw cycles. In contrast, a bimodal distribution of silver was observed. Due to high endogenous levels of iron, the migration pattern of these NPs could not be determined. Pyrosequence analysis of the bacterial communities revealed that there was no significant engineered NP-mediated decline in microbial richness. However, analysis of individual genera showed that Sphingomonas and Lysobacter were represented by fewer sequences in horizons containing elevated metal levels whereas there was an increase in the numbers of Flavobacterium and Niastella . Collectively, the results indicate that along with the differential migration behavior of NPs in the soil matrix, their impact on soil bacterial diversity appears to be dependent on environmental parameters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.001 |
| 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 teacher head, 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".