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Gastrointestinal Microbiota–Mediated Control of Enteric Pathogens

2014· review· en· W2161527837 on OpenAlexafffund
Sophie Yurist‐Doutsch, Marie‐Claire Arrieta, Stefanie Vogt, B. Brett Finlay

Bibliographic record

VenueAnnual Review of Genetics · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsBiologySalmonella entericaGastrointestinal tractMicrobiologyMicrobiomeImmune systemClostridium difficileInflammatory bowel diseaseSalmonellaGut floraImmunityImmunologyDiseaseBacteriaMedicineAntibioticsGenetics

Abstract

fetched live from OpenAlex

The gastrointestinal (GI) microbiota is a complex community of microorganisms residing within the mammalian gastrointestinal tract. The GI microbiota is vital to the development of the host immune system and plays a crucial role in human health and disease. The composition of the GI microbiota differs immensely among individuals yet specific shifts in composition and diversity have been linked to inflammatory bowel disease, obesity, atopy, and susceptibility to infection. In this review, we describe the GI microbiota and its role in enteric diseases caused by pathogenic Escherichia coli, Salmonella enterica, and Clostridium difficile. We discuss the central role of the GI microbiota in protective immunity, resistance to enteric pathogens, and resolution of enteric colitis.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.012
GPT teacher head0.309
Teacher spread0.297 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations65
Published2014
Admission routes2
Has abstractyes

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