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Record W2020729533 · doi:10.1128/jcm.03321-14

Molecular Profiling of Escherichia coli O157:H7 and Non-O157 Strains Isolated from Humans and Cattle in Alberta, Canada

2014· article· en· W2020729533 on OpenAlexafffundabout
Linda Chui, Vincent Li, Patrick Fach, Sabine Delannoy, Katarzyna Malejczyk, Laura Patterson-Fortin, Alan Poon, Robin King, Kimberley Simmonds, Allison N. Scott, Mao-Cheng Lee

Bibliographic record

VenueJournal of Clinical Microbiology · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsAgriculture Food and Rural DevelopmentProvincial Laboratory of Public HealthMinistry of HealthUniversity of Alberta
FundersAlberta Health Services
KeywordsEscherichia coliMicrobiologyBiologyProfiling (computer programming)EnterobacteriaceaeBacteriaGeneticsGene

Abstract

fetched live from OpenAlex

Virulence markers in Shiga toxin-producing Escherichia coli (STEC) and their association with diseases remain largely unknown. This study determines the importance of 44 genetic markers for STEC (O157 and non-O157) from human clinical cases and their correlation to disease outcome. STEC isolated from a cattle surveillance program were also included. The virulence genes tested were present in almost all O157:H7 isolates but highly variable in non-O157 STEC isolates. Patient age was a significant determinant of clinical outcome.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.434

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.308
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations29
Published2014
Admission routes3
Has abstractyes

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