Repeated Oral Vaccination of Cattle with Shiga Toxin-Negative Escherichia coli O157:H7 Reduces Carriage of Wild-Type E. coli O157:H7 after Challenge
Bibliographic record
Abstract
The bacterium E. coli O157:H7 causes foodborne disease in humans that can lead to bloody diarrhea, kidney failure, vascular damage, and death. Healthy cattle are the main source of this human pathogen. Reducing E. coli O157:H7 in cattle will reduce human disease. Using a randomized comparison, a bovine vaccine to reduce carriage of the human pathogen was tested. A detoxified E. coli O157:H7 strain, missing genes that cause disease, was fed to cattle as an oral vaccine to reduce carriage of pathogenic E. coli O157:H7. After vaccination, the cattle were challenged with disease-causing E. coli O157:H7. The vaccinated cattle had decreased E. coli O157:H7 during the first 7 days postchallenge and shed the bacteria for a shorter duration than the nonvaccinated control cattle. The results support optimization of the approach to cattle vaccination that would reduce human disease.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".