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Molecular Subtyping for <i>Escherichia coli</i> O157:H7 Isolated in Taiwan

2005· article· en· W2144461329 on OpenAlexaboutno aff
Tsung‐Yu Tsai, Wei‐Chen Luo, Fang‐Tzy Wu, Tzu‐Ming Pan

Bibliographic record

VenueMicrobiology and Immunology · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsnot available
FundersNational Taiwan UniversityNational Pingtung University of Science and Technology
KeywordsSubtypingBiologyEscherichia coliEscherichia coli ProteinsMicrobiologyComputational biologyGeneticsGeneProgramming languageComputer science

Abstract

fetched live from OpenAlex

Enterohaemorrhagic Escherichia coli O157: H7 is an important pathogen these days. Outbreaks of its infection have been reported all over the world, in Australia, Canada, Japan, the United States, south Africa, and various countries in Europe. In the summer of 2001, the first clinical infection by E. coli O157: H7 was identified in Taiwan. In this study, the standard procedures for molecular subtyping were applied to several strains collected in Taiwan as well as from elsewhere. The two molecular subtyping methods we used are pulsed-field gel electrophoresis (PFGE) and amplified fragment length polymorphism (AFLP). The isolates from the U.S.A., Canada, Japan, and Taiwan each showed a unique molecular fingerprinting pattern. The environmental strains isolated in Taiwan showed closer relationships with each other, and their similarity was in the range of 75-85%. The first clinical strain isolated in Taiwan in 2001 was similar to the strains from North America but not closely related to the Taiwanese environmental strains. Our surveys showed that some local E. coli O157: H7 strains did exist in Taiwan, but there had been only one official case report of the infection by local E. coli O157: H7. The eating habits of the people and the geographic distribution of the pathogen are considered crucial risk factors in Taiwan. The establishment of a database of our own and joining the global network database are important tasks if we want to control such agricultural and food-borne pathogens, and reduce the number of victims and amount sufferings, as well as the economic losses due to the infection.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.242
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2005
Admission routes1
Has abstractyes

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