Analysis of matrix effects critical to microbial transport in organic waste‐affected soils across laboratory and field scales
Bibliographic record
Abstract
Organic waste applications to soil (manure, various wastewaters, and biosolids) are among the most significant sources of bacterial contamination in surface and groundwater. Transport of bacteria through the vadose zone depends on flow path geometry and stability and is mitigated by interaction between soil, soil solution, air‐water interfaces, and characteristics of microbial surfaces. After initial entry, the transport through soil depends on continued entrainment of bacteria and resuspension of those retained in the porous structure. We evaluated the retention of bacteria‐sized artificial microspheres, varying in diameter and surface charge and applied in different suspending solutions, by a range of sieved soils contained in minicolumns, the transport of hydrophobic bacteria‐sized microspheres through undisturbed soil columns as affected by waste type under simulated rainfall, and the field‐scale transport of Enterococcus spp. to an unconfined sandy aquifer after the application of liquid manure. Microsphere retention reflected microsphere properties. The soil type and suspending solution affected retention of hydrophilic but not hydrophobic particles. Retention was not necessarily facilitated by manure‐microsphere‐soil interactions but by manure‐soil interactions. Undisturbed column studies confirmed the governing role of waste type on vadose‐zone microsphere transport. Filtration theory applied as an integrated analysis of transport across length scales showed that effective collision efficiency depended on the distance of travel. It followed a power law behavior with the power coefficient varying from ∼0.4 over short distances to >0.9 over 1 m (i.e., very little filtration for a finite fraction of biocolloids), consistent with reduced influence of soil solution and biocolloid properties at longer travel distances.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".