Analisis Proses Pembentukan Biogas dari Campuran Limbah Ikan, Kotoran Sapi dan Eceng Gondok (<i>Eichhornia Crassipes</i>)
Bibliographic record
Abstract
One of the biomass that can be used for making biogas is fish waste. Based on the research, fish waste has a small c / n ratio so it requires mixing with other organic materials that have a higher c / n ratio. The addition of water hyacinth and cow dung will increase the c / n ratio in the anaerobic process to make biogas. The aim of this research is to analyze the process anaerobically of biogas formation from a mixture of fish waste, cow dung, and water hyacinth. Biogas is made with a variation composition of cow dung (D1), a mixture of cow dung, water hyacinth, and fish waste (D2), and a mixture of cow dung and fish waste (D3).) The Variation ratio of each composition is 1: 0: 0; 5: 1: 1 and 2: 0: 1. The results are the value of volatile solid and total solid for each composition of D1, D2, D3 was 33,600 mg / L, 34,800 mg / L, 33,000 mg / L. Value of Total Solid D1, D2, D3 are 121,800 mg / L, 146,200 mg / L, 174,600 mg / L. Fermentation process lasts for 1 month at a temperature 25oC-33oC and pH 6-7. The rates of degradation of organic compounds for D1, D2, D3 are 0.0058/day; 0.0439/day and 0.0052/day.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".