A Field Guide for Monitoring Riverine Macroplastic Entrapment in Water Hyacinths
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
River plastic pollution is an environmental challenge of growing concern. However, there are still many unknowns related to the principal drivers of river plastic transport. Floating aquatic vegetation, such as water hyacinths, have been found to aggregate and carry large amounts of plastic debris in tropical river systems. Monitoring the entrapment of plastics in hyacinths is therefore crucial to answer the relevant scientific and societal questions. Long-term monitoring efforts are yet to be designed and implemented at large scale and various field measuring techniques can be applied. Here, we present a field guide on available methods that can be upscaled in space and time, to characterize macroplastic entrapment within floating vegetation. Five measurement techniques commonly used in plastic and vegetation monitoring were applied to the Saigon river, Vietnam. These included physical sampling, Unmanned Aerial Vehicle imagery, bridge imagery, visual counting, and satellite imagery. We compare these techniques based on their suitability to derive metrics of interest, their relevancy at different spatiotemporal scales and their benefits and drawbacks. This field guide can be used by practitioners and researchers to design future monitoring campaigns and to assess the suitability of each method to investigate specific aspects of macroplastic and floating vegetation interactions.
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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 | 0.000 | 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) | 0.001 | 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 it