Plastic Plants: The Role of Water Hyacinths in Plastic Transport in Tropical Rivers
Bibliographic record
Abstract
Recent studies suggest that water hyacinths can influence the transport of macroplastics in freshwater ecosystems at tropical latitudes. Forming large patches of several meters at the water surface, water hyacinths can entrain and aggregate large amounts of floating debris, including plastic items. Research on this topic is still novel and few studies have quantified the role of the water hyacinths in plastic transport. In this study, we present the findings of a six-week monitoring campaign, combining the use of visual observations and Unmanned Aerial Vehicle imagery in the Saigon river, Vietnam. For the first time, we provide observational evidence that the majority of macroplastic is transported by water hyacinth patches. Over the study period, these fast-growing and free-floating water plants transported 78% of the macroplastics observed. Additionally, we present insights on the spatial distribution of plastic and hyacinths across the river width, and the different characteristics of entrapped items compared with free-floating ones. With this study, we demonstrate the role of water hyacinths as a river plastic aggregator, which is crucial for improving the understanding of plastic transport, and optimizing future monitoring and collection strategies.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".