In-situ apparent conductivity measurements and microbial population distribution at a hydrocarbon-contaminated site
Bibliographic record
Abstract
Abstract We investigated the bulk electrical conductivity and microbial population distribution in sediments at a site contaminated with light nonaqueous-phase liquid (LNAPL). The bulk conductivity was measured using in-situ vertical resistivity probes; the most probable number method was used to characterize the spatial distribution of aerobic heterotrophic and oil-degrading microbial populations. The purpose of this study was to assess if high conductivity observed at aged LNAPL-impacted sites may be related to microbial degradation of LNAPL. The results show higher bulk conductivity coincident with LNAPL-impacted zones, in contrast to geoelectrical models that predict lower conductivity in such zones. The highest bulk conductivity was observed to be associated with zones impacted by residual and free LNAPL. Data from bacteria enumeration from sediments close to the resistivity probes show that oil-degrading microbes make up a larger percentage (5–55%) of the heterotrophic microbial community at depths coincident with the higher conductivity compared to ∼5% at the uncontaminated location. The coincidence of a higher percentage of oil-degrading microbial populations in zones of higher bulk conductivity suggests that the higher conductivity in these zones may result from increased fluid conductivity related to microbial degradation of LNAPL, consistent with geochemical studies that suggest that intrinsic biodegradation is occurring at the site. The findings from this study point to the fact that biogeochemical processes accompanying biodegradation of contaminants can potentially alter geoelectrical properties of the subsurface impacted media.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".