A Laboratory Dataset on Transport and Deposition of Spherical and Cylindrical Large Microplastics for Validation of Numerical Models
Bibliographic record
Abstract
The widespread presence of micro-sized plastic pollution has raised concerns due to their unique physical and toxic properties. Each year, water bodies carry millions of tons of plastic into the ocean. The inherent characteristics (such as size, shape, and density) of microplastics (MPs), along with flow factors like speed, depth, and pressure, significantly influence how MPs are transported and deposited. Therefore, this research aimed to gather experimental data on the transport and deposition of MPs to serve as a benchmark for numerical modeling. To achieve this goal, various test scenarios were set up in a straight channel flume to investigate different flow velocities, channel dimensions, and particle shapes. It was observed that cylindrical particles with the same density and similar size were more likely to become trapped compared to spherical particles. This study represents progress towards validating numerical models concerning the transport and deposition of microplastics.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".