Fluffy Rivers: How Our Clothes Can Harm Rivers and The Oceans
Bibliographic record
Abstract
Microplastics are one of the most well-known types of environmental pollution. A microplastic is any piece of plastic smaller than 5 mm (about the size of one of the circles on top of a Lego® block). Microplastics come in a variety of shapes and they can be eaten by even the smallest animals, blocking their stomachs and intestines. Many of the clothes that we wear are made from microplastic fibers. These fibers are released from our clothes when we wear and wash them, and they can eventually end up in the environment. We collected water samples from three rivers in the UK over 12 months, to see if they contained microplastic fibers. All the rivers contained clothing fibers, but most of the fibers were not made from plastics. Natural fibers made from materials like cotton (from plants) and wool (from sheep) were much more common than plastic fibers.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".