Evaluation of Vermicompost Produced by Using Post-Consumer Cotton Textile as Carbon Source
Bibliographic record
Abstract
A large amount of textile waste is generated every year around the globe. The textile product made from natural fibers might be vermicomposted and used as fertilizer. The present study aimed to research an integrated system of pre-composting (pathogen kill) and vermicomposting with various levels of post-consumer cotton waste to determine if this addition has any effects on the composting process. A vermicompost bin was constructed and filled with feedstocks mixed with post-consumer cotton textile waste at a 25:1 C:N ratio, and operated for three months at approximately 70% moisture content, with four composting trials with 0 g (control), 100 g, 200 g, and 300 g of textile waste. The pre-composting stage reached a temperature ranging from 40 °C to 50 °C, able to neutralize the pathogens. All four trials resulted in final compost with C: N ratios around 14, proving that post-consumer cotton textile waste did not affect the vermicomposting process, and was successfully used as a carbon source by worms to produce a healthy and mature compost. This indicates a sustainable option for the recovery of textile waste that is being decomposed in landfills.
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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) | 0.001 | 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".