Controls on Plastic Debris Capture in Urban Stormwater Drains of London, Canada: A Study Within the Great Lakes Watershed
Bibliographic record
Abstract
Land-based sources are the greatest contributors of plastic pollution in aquatic environments. Prior to this investigation, there were no available studies concerning the number and types of plastic debris items between 1 mm and 5 mm captured in urban stormwater drains. The present study examined macroplastic (>5 mm) and large microplastic (1-5 mm) debris that accumulated in LittaTrapTM devices at six drain sites over four seasonal periods in London, Ontario, Canada. Macroplastics (MaPs) and microplastics (MPs) were found in all 36 samples, and the totals ranged from 5-158 MaPs and 18-359 MPs per trap. Out of the 118 different MaPs found, the most common were cigarette butts, wrappers, and expanded polystyrene. The predominant MPs were fragments, foams, and fibres. Summer samples contained the highest average amounts of plastic. The main controls on plastic debris accumulation in stormwater drains of the London core are increased pedestrian traffic, driving, and seasonal variability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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".