Effect of thermotolerant bacterial inoculation on the microbial community during sludge composting
Bibliographic record
Abstract
A thermophilic bacterium (Geobacillus stearothermophilus CHB1) was inoculated in a sludge compost, and the effects of the inoculation on the abundance and structure of the bacterial community in the sludge compost were investigated using quantitative PCR and Illumina MiSeq sequencing. The results showed that the high-temperature stage (>50 °C) of the CHB1 and CK (control without inoculum) piles started on days 5 and 8, respectively, and lasted for 7 and 2 days, respectively, indicating the extension of the thermophilic phase by CHB1 inoculation in the sludge compost. At the end of composting, the CHB1 piles showed a higher loss of total organic carbon, lower C/N ratio, and lower moisture content. The abundance of bacteria in the CHB1 piles was significantly higher in the heating and thermophilic phase of composting but were lower than those of the CK in the cooling phase. The richness and diversity of the bacterial community in the thermophilic phase increased after inoculation with CHB1. After inoculation of CHB1, there were higher relative abundances of Firmicutes, Thermopolyspora, Thermobacillus, Thermomonas, Thermomonospora, and Thermovum, which can grow in a high-temperature environment. Furthermore, redundancy analysis indicated that total organic carbon, total nitrogen, C/N ratio, pH, temperature, and moisture were the significant parameters that affected the bacterial community structure during sludge composting. Our findings suggested that inoculation with CHB1 would enhance the quality and efficiency of composting.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".