Efficacy of Pleurotus eryngii Mycelium Containers as an Alternative to Current Single-Use Plastic Based Methods
Bibliographic record
Abstract
Introduction: The COVID-19 pandemic has led to an increase in takeout orders due to the mandated loss of dine-in options at restaurants. The significant rise in takeout has led to the use of single-use plastic containers that are currently made from materials such as polyethylene and expanded polystyrene (EPS). The aim of our research is to determine the effectiveness of Pleurotus eryngii (King oyster mushroom) based mycelium in replacing single-use takeout food containers. Methods: Variables such as flexural strength, permeability, insulation test, interactions between food and mycelium container, and decomposability in comparison to the common EPS takeout container. Various articles from scholarly sources such as PubMed, Google Scholar, and Omni library were used to determine the anticipated results. Results (hypothesized): The flexural strength test will be greater than or equal to 0.43 mPa. The mycelium container should be able to stop various viscosities of food from diffusing through the container due to the hydrophobicity of the mycelia. The mycelium should have greater insulation capacity than the standard EPS container. Qualitative observations obtained for interactions between the mycelium container and food should be similar to the control EPS container. Discussion: The mycelium container will be an effective alternative to using single-use EPS containers due to all tested variables resulting in the same or greater capabilities than the EPS container. Conclusion: Overall, using mycelium containers as an alternative to single use plastic takeout containers would reduce plastic waste and emission pollution, having a positive impact on climate change.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".