Lolium multiflorum germination and growth affected by virgin, naturally, and artificially aged high-density polyethylene microplastic and leachates
Bibliographic record
Abstract
With the detection of microplastics in soil, coupled with the various sources continuously contributing to its delivery to and distribution in soils, understanding the effects of microplastics on plants are necessary. Plastics discarded in the environment continually degrade into micro- and nano-sizes, subsequently leaching hazardous chemicals with time. Not only time but also environmental factors related to the climate of the area where the plastic is degrading will contribute to the breakdown process. Thus, this study aimed to understand the phytotoxic effects of microplastic derived from a frequently discarded plastic item, i.e., high-density polyethylene soda bottle caps. The commonly occurring perennial Lolium multiflorum (Italian ryegrass) was exposed to microplastic derived from new and artificially aged bottle caps as well as bottle caps collected from the cities of Lahti, Finland and Gqeberha, South Africa. Additionally, leachates were prepared from these samples and used for exposure. Germination, root and shoot growth, and fresh weight were measured as indicators of adverse effects, and various growth parameters were calculated. Microplastic and leachates from new and Lahti collected bottle caps adversely affected the germination and growth of the plant, indicating that aging and environmental factors affect the phytotoxicity of plastics as environmental pollutants in soil.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".