Mitigating microplastic exposure from water consumption in junior high students and teachers
Bibliographic record
Abstract
Microplastics (MPs) are inorganic material that have been observed within items destined for human consumption, including water, and may pose a potential health hazard. Here we estimated the average amount of MPs junior high students and teachers consumed from different water sources and determined whether promoting awareness of microplastic (MP) exposure influenced choice of water source and potential MPs consumed. We hypothesized that MP exposure from water would be approximately 40 MPs/day. We conducted three surveys of 57 students and 26 teachers from a junior high school in Calgary, Alberta, Canada, asking participants to estimate how much tap and bottled water they consumed. Following the first survey, participants were given an educational presentation on MPs and their potential effects. At baseline, participants consumed 4-6 L/day of water, mainly tap (≥90%), which translated into MP consumption ranging from 23-83 MPs/day. Males consumed more MPs/day than females, and adults more than students. Male students drank the most bottled water and had the highest MPs/day. Following the educational presentation, <10% of participants changed the source of water consumed. Microplastic consumption remained highest among male students (115.89 MP/day) who drank the most bottled water. Our study's pre- and post-presentation MP consumption estimates for all groups except male students were lower than recent Canadian research that estimated humans' annual MP intake. Although an educational presentation did not influence the source of water intake or MP exposure, individuals' willingness to participate in these surveys and increase MP awareness suggests an interest in reducing plastic exposure.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".