Evaluation of CO2 Emission From Rice Husk Biochar and Cowdung Manure Co-compost Preparation
Bibliographic record
Abstract
Composting of animal manure had been considered a sustainable alternative method for recycling organic waste. However the process involved had been associated with greenhouse gas emission (CO2, N2O and CH4) which play an active role in global warming. This study evaluated CO2 emissions from biochar-manure co-compost production. Biochar (from rice husk) and manure were mixed in a ratio of 3:1 v/v to achieve a range of different co-compost mixtures. The treatments and controls in triplicates of 18 units were arranged in a complete randomize design. All treatments were incubated at around 28 oC and turned every two days for 2 weeks, and later five days for 39 days. CO2 production in the compost bins was measured by trapping the evolved gas in 5M NaOH. Total CO2 emissions varied over time with higher rates at the beginning of the composting process. Within the first 7 days, total CO2 emissions (587 mg/m2) from cow dung alone was not significantly different from cow dung plus biochar (506 mg/m2). At the latter stages of the composting process, CO2 emission from cowdung and biochar mixture was less than from the other treatments.
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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".