Microplastics and Nanoplastics in Antarctica. Considerations on Their Impact on Ecosystems and Human and Fauna Health
Bibliographic record
Abstract
In recent years, microplastics and nanoplastics have been identified in a range of remote environments, including Antarctica.However, data throughout the Southern Hemisphere, particularly Antarctica, are largely absent.Microplastics and nanoplastics have negative effects on marine organisms and act as vectors for persistent organic pollutants and other toxic substances, which are harmful to aquatic environments and organisms.Microplastics and nanoplastics also pose serious problems for human health, especially due to its nanotoxic capacity, of which the mechanisms are not yet fully established.Microplastics and nanoplastics have been recognized as widespread pollutants in the marine environment and are known to be damaging to terrestrial and aquatic ecosystems, while their small size and relatively low density also allow them to become airborne and transported over large distances.This work summarizes the results of different research carried out by the various Antarctic programs in marine and terrestrial ecosystems of Antarctica.In addition, we analyze the knowlege about potencial nanotoxicity of nanoplastics and underscore the need for further research and development in this field.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".