MétaCan
Menu
Back to cohort

Intestinal Microbiota: A Regulator of Intestinal Inflammation and Cardiac Ischemia?

2015· review· en· W2141908915 on OpenAlexaff
Mohammad Bashashati, Hamid R. Habibi, Ali Keshavarzian, Max J. Schmulson, Keith A. Sharkey

Bibliographic record

VenueCurrent Drug Targets · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRegulatorInflammationIntestinal ischemiaIschemiaMedicineGut floraCardiologyImmunologyBiologyReperfusion injuryGeneticsGene

Abstract

fetched live from OpenAlex

Inflammatory bowel diseases (IBD) are chronic, relapsing and remitting gastrointestinal (GI) disorders of unknown etiology. IBD patients commonly exhibit extra-intestinal manifestations and complications of an inflammatory nature, presenting with disorders such as ankylosing spondylitis, uveitis and vasculitis. Although the metabolic syndrome is less prevalent in patients with IBD, they are at an increased risk for atherosclerosis and cardiovascular events. Considerable evidence supports the role of GI microbiota in the development of IBD. Recent studies have also shown a significant interaction between the metabolites of gut microbiota and the development of cardiovascular disease. Here we hypothesize that dysbiosis and/or abnormalities in the function of the intestinal microbiota promote cardiovascular disease in IBD patients, explaining the increased risk of cardiovascular events in these patients.

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 score0.010

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 studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.030
GPT teacher head0.328
Teacher spread0.298 · 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

Citations15
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Drug TargetsSame topicGut microbiota and healthFrench-language works237,207