The effects of temperature and duration of thermal pretreatment on the solid-state anaerobic digestion of dairy cow manure
Bibliographic record
Abstract
Cellulosic substrates such as dairy cow manure often yield low volumes of biogas and low concentrations of methane when digested anaerobically. Thermal pretreatment of dairy cow manure was investigated to determine if pretreatment temperature and duration can be optimized to maximize biogas yield and methane concentration. A central composite rotatable design was used to select combinations of temperature and duration. Based on measured data, statistical models were generated to estimate the biogas yield and methane concentration during digestion. The highest biogas yields were from the untreated samples and samples treated at the center temperature and duration of the statistical model (125 °C, 37.5 min). The model predicted the optimum pretreatment conditions of 140 °C for 30 minutes. Under the conditions of this experiment, temperature and duration had no significant effect on the biogas yield and methane concentration. This lack of significance may indicate that thermal pretreatment may be an unnecessary step in the anaerobic digestion of dairy cow manure, which could reduce capital and operating costs for the industry.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".