Nanoparticles as a younger member of the trace element species family — a food perspective
Bibliographic record
Abstract
Speciation analysis plays a key role in understanding the biological activity and toxicity of an element. So far, classical speciation analysis focused only on the dissolved fraction of an elemental species, whereas nanoparticle forms of analytes are being widely found in consumer and industrial products. A significant contributor to human exposure to nanoparticles is through food into which nanoparticles can be incorporated from endogenous sources or they may be formed naturally in the living organisms. Nanoparticles often undergo changes in the food matrices and upon consumption, in the gastrointestinal tract, which present a significant challenge to their characterisation. Therefore, a combination of both classical and nanoparticle speciation analytical techniques is needed for the characterisation of both dissolved and particulate forms of the chemical species. This article presents and discusses the current trends in analysis of nanoparticle behaviour in the gastrointestinal tract and formation and characterisation of biogenic nanoparticles.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".