Transport of bacteria in heterogeneous media under leaching conditions
Bibliographic record
Abstract
Bacterial mobility under unsaturated soils play an important role in the dispersal of pathogenic microorganisms and enhancing biorestoration of contaminated soil. Experiments were conducted to evaluate the effects of bacterial retention under unsaturated flow conditions in 5% and 10% bentonite–sand mixtures. Bacterial transport and retention was investigated under different rainfall events at 22°C and 4°C. Results indicated that bacterial accumulation was predominantly at the surface of the porous media and decreased with depth. Bacterial movement was also retarded relative to the chloride tracer in all fractions of the porous media. Heterogeneity of the porous media enhanced retention through filtration, specific surface area, and reduction in permeability. Recovery of the bacteria was influenced by the air–water interface with greater bacteria recovered at 4°C compared to 22°C. The colloidal filtration model described the distribution through the experimental columns. A linear relationship was observed between the filtration coefficient and the hydraulic conductivity from the different proportions of bentonite–sand. This correlation confirms that the colloidal filtration model can be used to determine the transport of bacteria through varying hydraulic conductivities of the porous media. Key words: porous media, hydraulic conductivity, retention, unsaturated flow, bacterial transport, filtration coefficient.
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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 | 0.000 | 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) | 0.000 | 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".