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Record W2123056400 · doi:10.1101/cshperspect.a009977

In Vitro and In Vivo Model Systems for Studying Enteropathogenic Escherichia coli Infections

2013· review· en· W2123056400 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCold Spring Harbor Perspectives in Medicine · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersMinistry of Health, State of IsraelNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaCanadian Institutes of Health ResearchHebrew University of Jerusalem
KeywordsEnteropathogenic Escherichia coliMicrobiologyBiologyIn vivoEscherichia coliIntiminDiarrheaIn vitroVirologyPathogenic bacteriaHost (biology)BacteriaEnterobacteriaceaeMedicineGene

Abstract

fetched live from OpenAlex

Enteropathogenic Escherichia coli (EPEC) and enterohemorrhagic E. coli (EHEC) belong to a group of bacteria known as attaching and effacing (A/E) pathogens that cause disease by adhering to the lumenal surfaces of their host's intestinal epithelium. EPEC and EHEC are major causes of infectious diarrhea that result in significant childhood morbidity and mortality worldwide. Recent advances in in vitro and in vivo modeling of these pathogens have contributed to our knowledge of how EPEC and EHEC attach to host cells and subvert host-cell signaling pathways to promote infection and cause disease. A more detailed understanding of how these pathogenic microbes infect their hosts and how the host responds to infection could ultimately lead to new therapeutic strategies to help control these significant enteric pathogens.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.918
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.350
Teacher spread0.300 · 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