Chemical Aspects of Nanoparticle Ecotoxicology
Bibliographic record
Abstract
Nanoecotoxicology strives to understand the processes and mechanisms by which engineered nanoparticles (ENP) may exert toxic effects on aquatic organisms. Detailed knowledge of the chemical reactions of nanoparticles in the media and of their interactions with organisms is required to understand these effects. The processes of agglomeration of nanoparticles, of dissolution and release of toxic metal ions, and of production of reactive oxygen species (ROS) are considered in this article. Important questions concern the role of uptake of nanoparticles in various organisms, in contrast to uptake of ions released from nanoparticles and to nanoparticle attachment to organism surfaces. These interactions are illustrated for effects of silver nanoparticles (AgNP), cerium oxide (CeO2 NP) and titanium dioxide (TiO2 NP), on aquatic organisms, including algae, biofilms, fish cells and fish embryos.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".