Pulmonary applications and toxicity of engineered nanoparticles
Bibliographic record
Abstract
Because of their unique physicochemical properties, engineered nanoparticles have the potential to significantly impact respiratory research and medicine by means of improving imaging capability and drug delivery, among other applications. These same properties, however, present potential safety concerns, and there is accumulating evidence to suggest that nanoparticles may exert adverse effects on pulmonary structure and function. The respiratory system is susceptible to injury resulting from inhalation of gases, aerosols, and particles, and also from systemic delivery of drugs, chemicals, and other compounds to the lungs via direct cardiac output to the pulmonary arteries. As such, it is a prime target for the possible toxic effects of engineered nanoparticles. The purpose of this article is to provide an overview of the potential usefulness of nanoparticles and nanotechnology in respiratory research and medicine and to highlight important issues and recent data pertaining to nanoparticle-related pulmonary toxicity.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".