Numbers of fecal streptococci and <i>Escherichia</i> <i>coli</i> in fresh and dry cattle, horse, and sheep manure
Bibliographic record
Abstract
Livestock are known contributors to stream pollution. Numbers of fecal streptococci and Escherichia coli in manure naturally deposited by livestock in the field are needed for activities related to bacterial source tracking and determining maximum daily bacterial loading of streams. We measured populations of fecal streptococci and E. coli in fresh and dry manure from cattle (Bos taurus L.), horses (Equus caballus L.), and sheep (Ovis aires L.) on farms in southern Idaho. Populations of indicator bacteria in dry manure were often as high as that in fresh manure from horse and sheep. There was a 2 log10 drop in the population of fecal coliform numbers in dry cattle manure from cattle in pastures but not from cattle in pens. Bacterial isolates used in source tracking should include isolates from both fresh and dry manure to better represent the bacterial source loading of streams.
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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 | 0.000 | 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".