Characterizing microplastic hazards: which concentration metrics and particle characteristics are most informative for understanding toxicity in aquatic organisms?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract There is definitive evidence that microplastics, defined as plastic particles less than 5 mm in size, are ubiquitous in the environment and can cause harm to aquatic organisms. These findings have prompted legislators and environmental regulators to seek out strategies for managing risk. However, microplastics are also an incredibly diverse contaminant suite, comprising a complex mixture of physical and chemical characteristics (e.g., sizes, morphologies, polymer types, chemical additives, sorbed chemicals, and impurities), making it challenging to identify which particle characteristics might influence the associated hazards to aquatic life. In addition, there is a lack of consensus on how microplastic concentrations should be reported. This not only makes it difficult to compare concentrations across studies, but it also begs the question as to which concentration metric may be most informative for hazard characterization. Thus, an international panel of experts was convened to identify 1) which concentration metrics (e.g., mass or count per unit of volume or mass) are most informative for the development of health-based thresholds and risk assessment and 2) which microplastic characteristics best inform toxicological concerns. Based on existing knowledge, it is recommended that microplastic concentrations in toxicity tests are calculated from both mass and count at minimum, though ideally researchers should report additional metrics, such as volume and surface area, which may be more informative for specific toxicity mechanisms. Regarding particle characteristics, there is sufficient evidence to conclude that particle size is a critical determinant of toxicological outcomes, particularly for the mechanisms of food dilution and tissue translocation .
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it