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Record W4406175909 · doi:10.1097/hc9.0000000000000622

Neurogastroenterology and motility disorders in patients with cirrhosis

2025· review· en· W4406175909 on OpenAlexaff
Francisco Idalsoaga, Gustavo Ayares, Hanna Blaney, Daniel Cabrera, Javier Chahuán, Hugo Monrroy, Ayah Matar, Houssam Halawi, Marco Arrese, Juan Pablo Arab, Luis Antonio Díaz

Bibliographic record

VenueHepatology Communications · 2025
Typereview
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsCirrhosisMedicineInternal medicinePsychological interventionQuality of life (healthcare)MotilityIntensive care medicinePopulationGastroenterologyPsychiatryEnvironmental healthBiology

Abstract

fetched live from OpenAlex

Neurogastroenterology and motility disorders are complex gastrointestinal conditions that are prevalent worldwide, particularly affecting women and younger individuals. These conditions significantly impact the quality of life of people suffering from them. There is increasing evidence linking these disorders to cirrhosis, with a higher prevalence compared to the general population. However, the link between neurogastroenterology and motility disorders and cirrhosis remains unclear due to undefined mechanisms. In addition, managing these conditions in cirrhosis is often limited by the adverse effects of drugs commonly used for these disorders, presenting a significant clinical challenge in the routine management of patients with cirrhosis. This review delves into this connection, exploring potential pathophysiological links and clinical interventions between neurogastroenterology disorders and cirrhosis.

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)0.001
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.311
Teacher spread0.290 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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