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Minimal hepatic encephalopathy: Consensus statement of a working party of the Indian National Association for Study of the Liver

2010· review· en· W1498881965 on OpenAlexaff
Radha K. Dhiman, Vivek A. Saraswat, Barjesh Kumar Sharma, Shiv Kumar Sarin, Yogesh Chawla, Roger F. Butterworth, Ajay Duseja, Rakesh Aggarwal, Deepak Amarapurkar, Praveen Sharma, Kaushal Madan, Samir Shah, Avnish Kumar Seth, Rakesh Gupta, Abraham Koshy, Jang B. Dilawari, Sri Prakash Mishra, Subrat Kumar Acharya

Bibliographic record

VenueJournal of Gastroenterology and Hepatology · 2010
Typereview
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsUniversité de MontréalHôpital Saint-Luc
Fundersnot available
KeywordsMedicineHepatic encephalopathyCirrhosisMandateNatural historyConsensus conferenceQuality of life (healthcare)EncephalopathySplenectomyGastroenterologyPsychiatryInternal medicineLawPolitical scienceNursing

Abstract

fetched live from OpenAlex

Hepatic encephalopathy (HE) is a major complication that develops in some form and at some stage in a majority of patients with liver cirrhosis. Overt HE occurs in approximately 30-45% of cirrhotic patients. Minimal HE (MHE), the mildest form of HE, is characterized by subtle motor and cognitive deficits and impairs health-related quality of life. The Indian National Association for Study of the Liver (INASL) set up a Working Party on MHE in 2008 with a mandate to develop consensus guidelines on various aspects of MHE relevant to clinical practice. Questions related to the definition of MHE, its prevalence, diagnosis, clinical characteristics, pathogenesis, natural history and treatment were addressed by the members of the Working Party.

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)0.011
metaresearch head score (Gemma)0.013
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0040.002
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0020.002

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 head0.050
GPT teacher head0.318
Teacher spread0.268 · 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

Citations141
Published2010
Admission routes1
Has abstractyes

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