Modelling microbial growth and biomass accumulation during methane oxidation in unsaturated soil
Bibliographic record
Abstract
Microbial aerobic methane oxidation (MAMO) affects methane emissions through landfill covers by not only consuming methane, but also causing biomass accumulation associated with bacterial growth. Although the reduction of soil porosity by biomass accumulation has been well recognized, most existing models ignore this effect when estimating MAMO efficiency. The present study proposes a newly improved theoretical model that could consider the effects of both microbial growth and biomass accumulation on MAMO during coupled water–gas–heat reactive transport in unsaturated soil. Comprehensive batch incubation tests were performed to determine the input parameters required. Part of a set of published experimental data was used to validate the new model, while the remainder of the dataset was used to evaluate the model predictability of soil–microbe interaction (i.e., class B prediction). When ambient temperature is relatively high (30 °C), ignoring biomass accumulation would lead to an overestimation of MAMO efficiency by more than three times. As the biomass accumulated in soil pores, the water permeability, gas permeability, and gas diffusion in the unsaturated soil reduced, consequently limiting the supply of oxygen to the bacteria for MAMO to take place.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".