Reservoirs of Extraintestinal Pathogenic <i>Escherichia coli</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Several potential reservoirs for the Escherichia coli strains that cause most human extraintestinal infections (extraintestinal pathogenic E. coli; ExPEC) have been identified, including the human intestinal tract and various non-human reservoirs, such as companion animals, food animals, retail meat products, sewage, and other environmental sources. Understanding ExPEC reservoirs, chains of transmission, transmission dynamics, and epidemiologic associations will assist greatly in finding ways to reduce the ExPEC-associated disease burden. The need to clarify the ecological behavior of ExPEC is all the more urgent because environmental reservoirs may contribute to acquisition of antimicrobial resistance determinants and selection for and amplification of resistant ExPEC. In this chapter, we review the evidence for different ExPEC reservoirs, with particular attention to food and food animals, and discuss the public health implications of these reservoirs for ExPEC dissemination and transmission.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it