Longitudinal Emergence and Distribution of <i>Escherichia coli</i> O157 Genotypes in a Beef Feedlot
Bibliographic record
Abstract
The purpose of this study was to describe the prevalence and longitudinal distribution of Escherichia coli O157 in feedlot cattle and the feedlot environment. Pen floors, water tanks, other cattle in the feedlot, feed, and bird feces were sampled for 2 weeks prior to entry of the study cattle. Twelve pens of study cattle were sampled twice weekly. At each sample time cattle feces, water from tanks in each pen, bunk feed, feed components, bird feces, and houseflies were collected. Bunk feed samples were collected before and after cattle had access to the feed. Overall, 28% of cattle fecal samples, 3.9% of bird fecal samples, 25% of water samples, 3.4% of housefly samples, 1.25% of bunk feed before calf access, and 3.25% of bunk feed samples after cattle had access to the feed were positive for E. coli O157. Genetic analysis of E. coli O157 isolates was done using pulsed-field gel electrophoresis (PFGE). PFGE types identified in sampling of the feedlot prior to calf entry were different than the majority of types identified following calf entry. A single strain type predominated in the samples collected after entry of the cattle. It was first identified 5 days after entry of the first pen of cattle and was subsequently identified in all pens. Data support that the incoming cattle introduced a new strain that became the predominant strain in the feedlot.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".