Thermodynamic constraints on methanogenic crude oil biodegradation
Bibliographic record
Abstract
Methanogenic degradation of crude oil hydrocarbons is an important process in subsurface petroleum reservoirs and anoxic environments contaminated with petroleum. There are several possible routes whereby hydrocarbons may be converted to methane: (i) complete oxidation of alkanes to H2 and CO2, linked to methanogenesis from CO2 reduction; (ii) oxidation of alkanes to acetate and H2, linked to acetoclastic methanogenesis and CO2 reduction; (iii) oxidation of alkanes to acetate and H2, linked to syntrophic acetate oxidation and methanogenesis from CO2 reduction; (iv) oxidation of alkanes to acetate alone, linked to acetoclastic methanogenesis and (v) oxidation of alkanes to acetate alone, linked to syntrophic acetate oxidation and methanogenesis from CO2 reduction. We have developed the concept of a 'window of opportunity' to evaluate the range of conditions under which each route is thermodynamically feasible. On this basis the largest window of opportunity is presented by the oxidation of alkanes to acetate alone, linked to acetoclastic methanogenesis. This contradicts field-based evidence that indicates that in petroleum rich environments acetoclastic methanogenesis is inhibited and that methanogenic CO2 reduction is the predominant methanogenic process. Our analysis demonstrates that under those biological constraints oxidation of alkanes to acetate and H2, linked to syntrophic acetate oxidation and methanogenesis from CO2 reduction offers a greater window of opportunity than complete oxidation of alkanes to H2 and CO2 linked to methanogenic CO2 reduction, and hence is the process most likely to occur.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".