Applications and environmental impacts of carbon-based nanoparticles and microparticles
Bibliographic record
Abstract
A visual depiction of the abstract for Chapter 2. IntroductionCarbon dots (CDs) are a class of fluorescent nanomaterials, typically less than ~10 nm in diameter, that can exhibit quantum dot-like behaviour.Since their initial discovery by Xu et al., 1 CDs are now seen as potential alternatives to traditional fluorescent dyes owing to their versatile optical properties and resistance to photobleaching. 2 They also exhibit lower toxicity (both cytoand chemical toxicity) in comparison to certain heavy metal-based quantum dots, 3 speaking to their potential for integration in biomedical applications.Early CD syntheses employed top-down approaches whereby graphite was processed through multiple steps using harsh chemicals to transform it into the more usable graphite oxide 4 before it was broken down into nano-sized CDs. 5 Bottom-up synthesis methods, whereby smaller molecules polymerize and carbonize to form CDs, are increasingly attractive due to their ease of implementation and tunability.Recent efforts exploit renewable raw materials (e.g., plants 6 ), or
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".