A Temperature-Guided Three-Stage Inoculation Method for Municipal Solid Wastes Composting
Bibliographic record
Abstract
Inoculation is a human-induced measure that can significantly enhance the composting process by increasing the initial microbial population, formulating viable microbial communities, and generating desired enzymes. However, the inoculation efficiency was usually subjected to competitions of indigenous microorganisms. In this study, a temperature-guided three-stage inoculation (TGTSI) method was developed to control the indigenous cell concentrations, and in turn, enhance the composting efficiency. The experimental results indicated that the TGTSI method could effectively suppress the initial cell concentrations of indigenous microorganisms, which resulted in significantly enhancement of biodegradations as well as the reduction of odor emissions. Moreover, a two-stage kinetics method was employed to analyze the TGTSI mechanisms. The model results were consistent with the experimental data. In conclusion, this study implied that TGTSI could not only enhance the composting process but also save system cost.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".