MétaCan
Menu
Back to cohort
Record W1495556587 · doi:10.1113/jphysiol.2014.273995

The microbiota–gut–brain axis in gastrointestinal disorders: stressed bugs, stressed brain or both?

2014· review· en· W1495556587 on OpenAlex
Giada De Palma, Stephen M. Collins, Přemysl Berčík, Elena F. Verdú

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.

Bibliographic record

VenueThe Journal of Physiology · 2014
Typereview
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsGut–brain axisMedicineNeuroscienceBiologyGut floraImmunology

Abstract

fetched live from OpenAlex

The gut-brain axis is the bidirectional communication between the gut and the brain, which occurs through multiple pathways that include hormonal, neural and immune mediators. The signals along this axis can originate in the gut, the brain or both, with the objective of maintaining normal gut function and appropriate behaviour. In recent years, the study of gut microbiota has become one of the most important areas in biomedical research. Attention has focused on the role of gut microbiota in determining normal gut physiology and immunity and, more recently, on its role as modulator of host behaviour ('microbiota-gut-brain axis'). We therefore review the literature on the role of gut microbiota in gut homeostasis and link it with mechanisms that could influence behaviour. We discuss the association of dysbiosis with disease, with particular focus on functional bowel disorders and their relationship to psychological stress. This is of particular interest because exposure to stressors has long been known to increase susceptibility to and severity of gastrointestinal diseases.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.830
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.028
GPT teacher head0.323
Teacher spread0.295 · 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