Soil microbial populations, community composition, and activity as affected by repeated applications of hog and cattle manure in eastern Saskatchewan
Bibliographic record
Abstract
A field site near Humboldt, Saskatchewan, was annually treated with hog or cattle manure and cropped to canola, spring wheat, barley, and canola from 1997 to 2000. During each growing season, soil was analyzed for microbial populations in terms of activity and community structure, and crops were assessed for root rot and foliar diseases. Microbial activity in soils treated with cattle manure was higher than in soils treated with hog manure or urea. Similarly, nitrous oxide emissions from soil increased with increasing rates of hog and cattle manure. Potential human pathogens, including Rahnella, Serratia, Proteus, Leclercia, and Salmonella species, were identified in soils that received cattle manure, whereas pseudomonads were the dominant species in the hog-manure-treated soil. Fecal coliforms were confirmed in soils that received hog or cattle manure. However, Enterobacteriaceae populations were 10-fold higher in soils receiving cattle manure than in soils receiving the other treatments. Increasing cattle manure rates increased fecal coliform population, but there was no indication that increased hog manure rates increased fecal coliform populations. Addition of urea, hog manure, or cattle manure to the soil did not increase foliar disease in wheat, barley, and canola and had variable effects on root rot incidence in cereals.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".