Selection and Characterization of Microbial Communities to Improve Swine manure methansiation at Low Temperature
Bibliographic record
Abstract
Psychrophilic anaerobic digestion may offer many advantages for livestock farms in temperate climate but it is limited by the long time required for microbial community adaptation to low temperature. The first part of this study focused on selecting a so called psychrophilic inoculum producing methane at 13°C. Among 4 different manure sources, stored swine manure gave the best result with a yield of 42 L CH4/kg VSsubstrate·day after a 9 month period of acclimation. The second part of the study focused on the understanding of archaeal communities' adaptation of this psychrophilic inoculum to temperature changes (35° - 25°C - 15°C - 5°C). Methane production rates were monitored and coupled with archaeal community analysis to link microbial populations to methane production. The results show that adaptation to low temperature requires archaeal populations' shifts within the community with species potentially better fitted to lower temperatures.
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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 | 0.001 | 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 | 0.001 |
| 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".