Strategies for reducing ocean plastic debris should be diverse and guided by science
Bibliographic record
Abstract
Abstract Studies suggest that trillions of microplastic particles are floating on the surface of the global oceans and that the total amount of plastic waste entering the ocean will increase by an order of magnitude by 2025. As such, this ever-increasing problem demands immediate mitigation and reduction. Diverse solutions have been proposed, ranging from source reduction to ocean-based cleanup. These solutions are most effective when guided by scientific evidence. A study published in Environmental Research Letters (Sherman and van Sebille 2016 Environ. Res. Lett. 11 014006 ) took a closer look at the potential effectiveness of ocean-based cleanup. They conclude that it will be most cost-effective and ecologically beneficial if clean-up efforts focus on the flux of microplastics from the coasts rather than in the center of the oceans where plastic accumulates in so called ‘garbage patches’. If followed, this example may become one of a series of examples where science has informed a solution to the complex problem of plastic pollution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".