Organic Matter Degradation in Energy-Limited Subsurface Environments—A Bioenergetics-Informed Modeling Approach
Bibliographic record
Abstract
Microbial degradation of organic matter is a key driver of subsurface biogeochemistry. Here, we present a bioenergetics-informed kinetic model for the anaerobic degradation of macromolecular organic matter that accounts for extracellular hydrolysis, fermentation, and respiration. The catabolic energy generated by fermentation and respiration is allocated to biomass growth, production of extracellular hydrolytic enzymes, and cellular maintenance. Microbial cells are assumed to exist in active or dormant states with marked differences in maintenance energy requirements. Dormant cells are further assumed to fulfill their maintenance energy requirements by utilizing their own biomass instead of relying on external substrates. When the catabolic Gibbs energy production for a given functional group of microorganisms exceeds the total maintenance energy requirement of the active cells, biomass growth, re-activation of dormant cells, and production of extracellular hydrolytic enzymes are possible. The latter, in turn, allows the microbial community to access more of the available external organic substrates. In the opposite case, active cells decay or become dormant. We apply the model to simulate the anaerobic degradation of cellulose by a hypothetical microbial community consisting of cellulolytic fermenting bacteria and sulfate-reducing bacteria, under conditions representative of those encountered in water-saturated subsurface environments.
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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) | 0.005 | 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".