Rural plastic emissions into the largest mountain lake of the Eastern Carpathians
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
The lack of proper waste collection systems leads to plastic pollution in rivers in proximity to rural communities. This environmental threat is more widespread among mountain communities which are prone to frequent flash floods during the warm season. This paper estimates the amounts of plastic bottles dumped into the Izvoru Muntelui lake by upstream rural communities. The plastic pollution dimension between seasonal floods which affected the Bistrita catchment area during 2005-2012 is examined. The floods dumped over 290 tonnes of plastic bottles into the lake. Various scenarios are tested in order to explain each amount of plastic waste collected by local authorities during sanitation activities. The results show that rural municipalities are responsible for 85.51% of total plastic bottles collected during 2005-2010. The source of plastic pollution is mainly local. The major floods of July 2008 and June 2010 collected most of the plastic bottles scattered across the Bistrita river catchment (56 villages) and dumped them into the lake. These comparisons validate the proposed method as a reliable tool in the assessment process of river plastic pollution, which may also be applied in other geographical areas. Tourism and leisure activities are also found to be responsible for plastic pollution in the study area. A new regional integrated waste management system should improve the waste collection services across rural municipalities at the county level when it is fully operational. This paper demonstrates that rural communities are significant contributors of plastics into water bodies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| 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