Empirical Buswell’s Equation for Identifying Anaerobic Digestate
Bibliographic record
Abstract
Anaerobic digestion is a promising circular economic technology. Using organic matters as feedstocks, Buswell’s equation can represent anaerobic digestion in accordance with the elemental composition of any organic matter. An organic feedstock is biodegradable to biomethane, biogenetic carbon dioxide, and digestate, but the management of anaerobic digestate encounters some environmental and technological challenges. Currently there is a research gap between Buswell’s concept and the general organic elemental composition of unknown anaerobic digestate. To bridge the gap, this research developed an empirical Buswell’s equation for identifying anaerobic digestate through the integration of theoretical Buswell’s equation and experimental biomethane potential. This model can identify the organic elemental composition and characteristics of any anaerobic digestate, as well as reveal the correlation between an organic matter and its anaerobic digestate. It also discovers a higher heat value of anaerobic digestate which is greater than that of its corresponding organic matter. In addition, the empirical Buswell’s equation can be used for assessing the validity of the empirical formula of organic feedstock.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".