Characterization of Engineered Cerium Oxide Nanoparticles and Their Effects on Lung and Macrophage Cells
Bibliographic record
Abstract
Cerium oxide nanoparticles are promising materials as novel nanoscale therapeutics and are commonly used materials in industrial processes. Most cytotoxicity studies on cerium oxide nanoparticles are made from in-lab prepared materials making comparison between studies challenging, especially when performed on unique cell lines under non-standard conditions. Using commercially available nanoparticles we show that particle stability/agglomeration may be critical in determining the cytotoxicity in some cell lines, while in other cell lines, larger sized primary particles are linked to higher cytotoxicity, contrasting what has been reported in the literature for smaller cerium nanoparticles. To accelerate the development of cerium oxide enabled commercial processes and biomedical innovations, a clearer understanding of the interactions between cerium oxide nanoparticles and cells is needed to better understand their fate in and impact on biological systems.
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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 | 0.000 | 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 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".