Application of a dual deposition mode model to evaluate transport of <i>Escherichia coli</i> D21 in porous media
Bibliographic record
Abstract
Controlled laboratory‐scale column deposition experiments were conducted using a well‐characterized mutant of the Escherichia coli (E. coli) K12 strain to obtain insight into the mechanisms that give rise to the observed deviation from classical colloid filtration theory (CFT). Both the suspended effluent bacteria concentration and the spatial distribution of retained bacteria were systematically measured over a wide range of solution conditions using columns packed with spherical glass beads. Calculations of Derjaguin–Landau–Verwey–Overbeek (DLVO) interaction energies based on measured cell zeta potentials indicated that the bacteria should experience considerable repulsive interaction forces when approaching the glass bead surface. In spite of these predictions, bacterial adhesion was observed even at the lowest solution ionic strength investigated (3 mM) and increased with solution salt concentration. Comparison of these results with measurements obtained using model colloidal particles (polystyrene latex microspheres) and a different microbe (Cryptosporidium parvum) suggested that another non‐DLVO‐type interaction may be contributing to the observed deposition behavior. Furthermore, predictions based on a discrete dual deposition mode (DDM) model disagreed with measured fractions of released cells. Taken together, the experimental and modeling results suggest that the deposition behavior of bacteria in saturated porous media is influenced by additional interaction mechanism(s) or factors not considered in classical DLVO theory, such as local charge heterogeneities of the cell membrane and surface biomolecule‐specific interactions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".