MICROPLASTICS AND THE IMPORTANCE OF REDUCING THEM FOR THE BENEFIT OF HEALTH
Bibliographic record
Abstract
The objective of this documentary research is to carry out an analysis of the negative impact on health caused by daily use plastics that are not legislated.Currently, government regulations are prohibiting single-use plastic bags but do not pay attention to other types of plastics that have direct contact with humans, such as baby bottles, personal thermoses, bottled water that sells for millions, glasses, etc...The use of this type of products causes the direct ingestion of the microplastics that are released from them.In studies carried out on blood samples, plastic particles were found in 77% of them and of these, half corresponded to PET and 25% to styrene polymers.It is estimated that bottled water and food products extracted from the sea near the coast are the most contaminated.The danger of microplastics lies in their weight and size, which are tiny because they can adhere to red blood cells, limiting oxygen transport.They can be in the placentas of pregnant women and in babies' bottles.To prevent and counteract the use of any type of plastics, the government must legislate its use in a comprehensive manner and civil society must raise awareness through campaigns on social networks, talks, forums, among others, to be more proactive and be aware of their negative impact.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".