Persistent, mobile, and toxic plastic additives in Canada: properties and prioritization
Bibliographic record
Abstract
The hazards of many plastic additives on human and environmental health are well documented. However, little emphasis has been put on plastic additives that are persistent, mobile, and toxic (PMT) rather than persistent, bioaccumulative, and toxic. Due to their high mobility and stability, it is unlikely that wastewater treatment plants will effectively remove PMT plastic additives. Herein, an in silico analysis was performed to (1) assess the retention of PMT plastic additives registered for use in Canada in wastewater treatment plants; and (2) determine whether their physical–chemical properties and structural features can be used as identifiers for PMT plastic additives with particularly low retention. We identified 124 PMT plastic additives of which 52% had less than 20% removal from wastewater treatment based on predictions using the model SimpleTreat. Log Kaw, log Kow/Dow, and log Koc/Doc ranges were defined that are indicative of low retention PMT plastic additives. Furthermore, it was found that non-halogenated PMT plastic additives that contain nitrogen are most likely to be poorly retained in wastewater treatment plants. The results of this study provide screening and prioritization criteria, as well as a suspect list for PMT plastic additives.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".