The Medical Significance of Shiga Toxin-Producing Escherichia coli Infections: An Overview
Bibliographic record
Abstract
Shiga toxin (Stx)-producing Escherichia coli (STEC), also referred to as Verocytotoxin-producing E. coli (VTEC) (), are causes of a major, potentially fatal, zoonotic food-borne illness whose clinical spectrum includes nonspecific diarrhea, hemorrhagic colitis, and the hemolytic uremic syndrome (HUS) (, , , , ). The occurrence of massive outbreaks of STEC infection, especially resulting from the most common serotype, O157:H7, and the risk of developing HUS, the leading cause of acute renal failure in children, make STEC infection a public health problem of serious concern (,,). Up to 40% of the patients with HUS develop long-term renal dysfunction and about 3–5% of patients die during the acute phase of the disease (, , , ). There is no specific treatment for HUS, and vaccines to prevent the disease are not yet available. The purpose of this overview is to highlight the public health impact, epidemiology, and clinicopathological features of STEC infection.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".