Epidemiologic Subtyping of <i>Escherichia coli</i> Serogroup O157 Strains Isolated in Ontario by Phage Typing and Pulsed-Field Gel Electrophoresis
Bibliographic record
Abstract
Phage typing and DNA macrorestriction fragment analysis by pulsed-field gel electrophoresis (PFGE) were evaluated for use in the epidemiological subtyping of Escherichia coli serogroup O157 strains isolated in Ontario, Canada. Among 30 strains isolated from patients with sporadic cases of infection, 22 distinct XbaI macrorestriction patterns were identified and 17 strains exhibited unique PFGE patterns. In contrast, phage typing identified only seven different phage types and 17 strains belonged to the same phage type. A total of 25 phage type-macrorestriction pattern combinations were identified among the strains from patients with sporadic cases of infection. PFGE subtyping differentiated between unrelated strains that exhibited the same phage type, and in one group of strains, phage typing differentiated between strains of the same PFGE subtype. Both typing procedures correctly identified outbreak-related isolates as belonging to the same type in four separate outbreaks. Each outbreak strain was characterized by a distinct macrorestriction pattern, while phage typing subdivided the outbreak strains into only three different types. A small percentage of outbreak-related isolates had PFGE patterns that differed slightly (one or two DNA fragment differences) from that of the outbreak strain. On the other hand, each isolate from the same outbreak belonged to the same phage type as that of the outbreak strain. We conclude that phage typing and PFGE fingerprinting represent complementary procedures for the subtyping of E. coli serogroup O157 and that the combined use of these procedures provides optimal discrimination.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".