Biological Clogging in Compacted Mixtures of Ottawa Sand and Kaolinite
Bibliographic record
Abstract
Biological clogging of porous media by metabolically active bacteria is an important issue in Geoenvironmental engineering. In this paper, the role of two important factors influencing biological clogging is evaluated. Results are presented from two different series of percolating experiments: (1) experiments conducted with sterile and unsterile soil, (2) experiments conducted with soils subjected to low and high hydraulic head. A. mixture of Ottawa sand and Kaolinite was used as the porous medium and Pseudomonas aeruginosa as the bacterial culture. Results indicated that filtering as well as clogging by bacteria occurred in soil samples, as reflected by the reduction in the CFUs (Colony Forming Units) of the effluent compared to the influent CFUs. Comparisons of pore size distributions (PSD) of the soil before and after clogging revealed that both biomass growth and biogas generation were responsible for the permeability reduction. Experiments conducted with sterile and unsterile soil revealed that higher reduction in permeability could be achieved in unsterile soil because of the presence of indigenous soil microbes. Experiments conducted with sample subjected to high hydraulic head revealed that high heads would result in biofilm rupture formed on the surface, which would result in subsequent increase in permeability.
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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 | 0.001 |
| 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 | 0.001 | 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".