Microplastics found in the World Heritage Site Cocos Island National Park, Costa Rica
Bibliographic record
Abstract
Microplastics (MPs) defined as ‘small’ pieces of plastic < 5 mm have been found in almost every marine habitat around the world, and studies have shown that we can find them in the ocean surface, the water column, the seafloor, the shoreline, in biota and in the atmosphere-ocean interface. This study aimed to assess both marine and freshwater environments of Cocos Island, Costa Rica, in the Pacific Ocean, by sampling sediments and biota to determine the presence and abundance of this pollutant. Sediment samples were superficial and weighed one kilogram each. For the sampling of freshwater fish and shrimps, nonselective capture with small nets was made in rivers with access by land, while fishing rods were used for the marine fish sampling, and cage and scuba diving for lobsters. Plastics were found in all types of samples: 93% of marine sediments, 32% of freshwater sediments, 20% of freshwater fish, 15% of freshwater shrimps, 27% of marine fish, and 51% of marine lobsters. Like many reports around the world, it was expected to find MPs at marine samples, and it was concluded that ocean currents, tourism activities, and discarded fishing gear from illegal fishing activities could be the sources of marine pollutants. In contrast, the amount of MPs found in freshwater environments was not expected. Their possible sources are unclear at this moment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".