Co-occurrence patterns among prokaryotes across an age gradient in pit mud of Chinese strong-flavor liquor
Bibliographic record
Abstract
It is widely believed that the quality and characteristics of Chinese strong-flavor liquor (CSFL) are closely related to the age of the pit mud; CSFL produced from older pit mud tastes better. This study aimed to investigate the alteration and interaction of prokaryotic communities across an age gradient in pit mud. Prokaryotic microbes in different-aged pit mud (1, 6, and 10 years old) were analyzed by Illumina MiSeq sequencing of the 16S rRNA gene. Analysis of the 16S rRNA gene indicated that the prokaryotic community was significantly altered with pit mud age. There was a significant increase in the genera Methanosarcina, Methanobacterium, and Aminobacterium with increased age of pit mud, while the genus Lactobacillus showed a significant decreasing trend. Network analysis demonstrated that both synergetic co-occurrence and niche competition were dominated by 68 prokaryotic genera. These genera formed 10 hubs of co-occurrence patterns, mainly under the phyla Firmicutes, Euryarchaeota, and Bacteroidetes, playing important roles on ecosystem stability of the pit mud. Environmental variables (pH, NH 4 + , available P, available K, and Ca 2+ ) correlated significantly with prokaryotic community assembly. The interaction of prokaryotic communities in the pit mud ecosystem and the relationship among prokaryotic communities and environmental factors contribute to the higher quality of the pit mud in older fermentation pits.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 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".