A microbial fuel cell in contaminated ground delineated by electrical self‐potential and normalized induced polarization data
Bibliographic record
Abstract
There is a growing interest in the use of geophysical methods to aid investigation and monitoring of complex biogeochemical environments, for example delineation of contaminants and microbial activity related to land contamination. We combined geophysical monitoring with chemical and microbiological analysis to create a conceptual biogeochemical model of processes around a contaminant plume within a manufactured gas plant site. Self‐potential, induced polarization and electrical resistivity techniques were used to monitor the plume. We propose that an exceptionally strong (>800 mV peak to peak) dipolar SP anomaly represents a microbial fuel cell operating in the subsurface. The electromagnetic and electrical geophysical data delineated a shallow aerobic perched water body containing conductive gasworks waste which acts as the abiotic cathode of microbial fuel cell. This is separated from the plume below by a thin clay layer across the site. Microbiological evidence suggests that degradation of organic contaminants in the plume is dominated by the presence of ammonium and its subsequent degradation. We propose that the degradation of contaminants by microbial communities at the edge of the plume provides a source of electrons and acts as the anode of the fuel cell. We hypothesize that ions and electrons are transferred through the clay layer that was punctured during the trial pitting phase of the investigation. This is inferred to act as an electronic conductor connecting the biologically mediated anode to the abiotic cathode. Integrated electrical geophysical techniques appear well suited to act as rapid, low cost sustainable tools to monitor biodegradation.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".