Case Study Comparing Effects of Microplastic Derived from Bottle Caps Collected in Two Cities on Triticum aestivum (Wheat)
Bibliographic record
Abstract
As plastic has become an integral component of daily life, microplastic has become a ubiquitous, unavoidable constituent of nearly all ecosystems. Besides monitoring the amount and distribution of microplastic in the environment, it is necessary to understand the possible direct effects, especially toxicity and how it is affected by environmental factors where it is discarded. The present study investigated how microplastic derived from high-density polyethylene bottle caps collected in two climatically different cities, i.e., Singapore (tropical rainforest climate) and Lahti, Finland (continental climate), affected the essential agricultural grain crop, Triticum aestivum (L.). Wheat seedlings were exposed to microplastic derived from these collected bottle caps, as well as new and artificially aged caps, for seven days. Morphological parameters, such as root and shoot length and oxidative stress development, were measured. Exposure to microplastic derived from the caps resulted in reduced seedling root and shoot lengths compared to the controls, as well as enhanced lipid peroxidation and catalase activity. With all parameters tested, microplastic derived from Lahti bottle caps exhibited more severe effects than Singapore, which was similar to that elicited by new microplastic. The Singapore microplastic had possibly leached its toxic substances before collection due to accelerated degradation promoted by the prevailing warmer climate conditions.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".