Dynamics of <i>Escherichia coli</i> in agricultural soils receiving swine manure slurry or liquid municipal biosolids
Bibliographic record
Abstract
The fate of two E. coli stains, one that grows in soil receiving swine manure slurry (SMS) (Strain C279) and one that does not (Strain C278) were evaluated in laboratory and field experiments. A sensitive (detection limit 5 cells g soil-1) microplate-format most probable number (MPN) method for enumerating E. coli was developed and validated. In laboratory incubations, there was a general relationship between manure volatile fatty acid (VFA) content and the ability of the SMS to support growth in soil. Strain C279 grew in SMS-amended loam or sandy soil, but not in silt loam soil. Swine manure slurry inoculated with both Strains C278 and C279 was surface or subsurface applied in field microplots. The population of E. coli increased 50-fold within 3 d, and the ratio of Strain C279 to Strain C278 increased as much as 20-fold during the experiment, consistent with the growth of Strain C279 under these circumstances. Liquid municipal biosolids (LMB) obtained from four cities did not support the growth of Strain C279. The dynamics of E. coli populations in soils receiving surface and subsurface (10 cm) applications of SMS were comparable. Key words: Escherichia coli, water quality, liquid municipal biosolids, swine manure slurry
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".