Influence of a nanoparticle mixture on an arctic soil community
Bibliographic record
Abstract
Interest is growing in understanding not only the impact of individual nanoparticles (NPs) on ecosystems but also the effect of NP mixtures. In the present study, the impact of a combination of three different NPs, silver, copper, and silica (all at 0.022%, w/w), on an arctic microbial community was investigated. After adding the NPs, soil microcosms were incubated for 176 d, and subsequent estimates of microbe diversity were obtained using culture-dependent and culture-independent assessments. The treated soil appeared to show a reduction in the ability to use carbohydrate and amino acid substrates and demonstrated an altered pattern of major fatty acid peaks. Polymerase chain reaction-denaturing gradient gel electrophoresis showed consistent differences in the pattern of predominant rRNA gene sequences. Although this is an initial investigation of soil contaminated with mixed NPs, these results demonstrate that even at the relatively modest concentrations used such pollutants have the potential to disrupt microbial communities.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".