Microplastics and Environmental Health: Assessing Environmental Hazards in Haiti
Bibliographic record
Abstract
Microplastics (MP) refer to all plastic particles that are less than 5 mm in size. Over the past decades, several studies have highlighted the impact of microplastics (MP) on living organisms. In addition to being pollutants themselves, these synthetic polymers also act as vectors for the transport of various types of chemicals in natural ecosystems. MP has been ubiquitously detected in a wide range of shapes, polymers, sizes and concentrations in marine water, freshwater, agroecosystems, atmospheric, food and water environments. Drinking water, biota, and other remote places. According to the World Bank, over 80% of the world’s marine litter is plastic and the concentration of litter on Caribbean beaches is often high, with a high presence of single-use plastics and food containers. In its work, the World Health Organization (WHO) suggests an in-depth assessment of microplastics present in the environment and their potential consequences on human health, following the publication of an analysis of the state of research on microplastics in drinking water. It also calls for reducing plastic pollution to protect the environment and reduce human exposure. In Haiti, the bay of Port-au-Prince is the natural receptacle of all the urban effluents generated by human activities in the Metropolitan Zone. This urban wastewater carries household waste, sludge from pit latrines and sewage, industrial wastewater which largely contributes to the pollution of the bay. Furthermore, 1,673,750 tonnes per year of household waste, including 93,730 tonnes of plastic waste, are not collected. What are the environmental dangers represented by the MP contained in those wastes for living organisms in exposed tropical ecosystems? The purpose of this paper is: (i) to do a bibliographical review of the physical and chemical properties, as well as the toxicological profile of MP, (ii) to identify the environmental hazards associated with MP contained in urban waste in the metropolitan area of Port-au-Prince.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".