Bibliographic record
Abstract
With growing concerns over plastic accumulation in the environment, it is imperative to quantify nanoplastic and microplastic release to water bodies via water treatment plant effluent streams. Current methodological limitations present a major challenge for continuous monitoring of nanosized pollutants in effluent streams. In this work, a novel correlation was established between removal of nanoplastics and total suspended solids (TSS) during aggregation-based wastewater treatment. The established correlation successfully predicted nanoplastic removal for a wide range of relevant nanoplastic properties, including polymer type, size, surface functionalization and ageing history, under 41 different physico-chemical and activated sludge treatment conditions (R2 = 0.92; n = 117). The results of our correlation reveal a predicted nanoplastic removal between 39% and 69% for typical water treatment effluent streams governed by current TSS regulations in North America. The study also reveals the potential of using TSS as a simple metric to estimate microfibre, microsphere and microfragment removal.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 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".