Performance of food-waste compost biocovers in mitigating methane emission from landfills
Bibliographic record
Abstract
This paper presents the results of an experimental programme that was employed to investigate the performance of biocovers made of food-waste compost in mitigating methane emissions from municipal solid waste landfills in a semi-dry environment. Five experimental columns containing biocover materials made of compost mixed with landfill intermediate cover soil at different compost/soil mixture ratios were exposed to methane inflow under ambient temperature over a period of 3 months. Methane removal efficiencies were determined based on methane content measurements using gas chromatography, bacterial count and scanning electron microscopy performed on biocover samples over time. The biocover materials made of 70% compost and 30% soil demonstrated significantly higher methane removal efficiencies compared with other mixtures, measuring an emission reduction of about 63%. The compost type and composition were also found to affect the methane removal efficiency of biocover materials. These findings can be used for selection of compost type and compost/soil mixture ratio as biocover materials.
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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".